lead data engineer

Lakeview Loan Servicing

<div>Overview:
<div>
The Lead Data Engineer on the Nebula team plays a significant technical leadership role in shaping and scaling the data foundation that powers analytics, reporting, AI development, and operational decision-making across the organization. This role combines hands-on data engineering execution with practical team leadership, helping the organization build reliable, flexible, and production-ready data systems.</div><div></div><div> 
The Lead Data Engineer heads a lean, high-caliber squad of data engineers, while remaining deeply hands-on in the design, development, and operation of core data systems. The role balances direct technical contribution with mentoring, coaching, coordination, and day-to-day support for the engineers on the squad.</div><div></div><div> 
Working across ingestion, transformation, storage, modeling, orchestration, and delivery, this role partners closely with Product, Engineering, AI, Analytics, and domain Subject Matter Experts (SMEs) to translate complex business processes into scalable data platforms, pipelines, and trusted datasets.</div><div></div><div> 
This role owns the technical direction for core data capabilities, including ETL/ELT, batch and real-time processing, OLTP and OLAP systems, BI-ready data models, and cloud-based data infrastructure in a regulated, high-stakes environment. Success requires strong architectural judgment, operational discipline, and the ability to raise the technical bar for both systems and people.</div><div></div><div> 
This is a fully remote position that offers a competitive salary range of $220,000 to $300,000, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors.</div>
Responsibilities:
<div>
Strategic Technical Leadership</div><ul><li>
Own the architecture and evolution of core data systems, including ingestion, transformation, orchestration, storage, modeling, and delivery layers</li><li>
Set technical direction for ETL/ELT, batch processing, real-time pipelines, OLTP and OLAP systems, and BI-ready data assets</li><li>
Make pragmatic architecture decisions that balance scalability, reliability, security, performance, cost, and delivery speed</li><li>
Establish engineering standards, reusable patterns, and design principles that improve quality and leverage across the data platform</li></ul>
Hands-On Data Engineering Delivery<ul><li>
Lead the design, build, rollout, and operations of greenfield data infrastructure</li><li>
Build and maintain complex data pipelines across diverse source and destination systems, including databases, APIs, files, SaaS platforms, event streams, and internal applications</li><li>
Design and optimize data models, warehouse schemas, semantic layers, and curated datasets for analytics, reporting, AI, and product use cases</li><li>
Contribute directly to critical implementation work, including writing code, code and design reviews, migrations, reliability improvements, and production issue resolution</li></ul>
Squad Leadership &amp; Management<ul><li>
Lead a lean, high-caliber squad of data engineers, spending focused time mentoring, coaching, managing, and coordinating the team</li><li>
Develop engineers through regular feedback, technical guidance, code reviews, career support, and clear expectations around quality and ownership</li><li>
Help prioritize team work, clarify scope, remove blockers, and ensure the squad delivers reliably against business and technical goals</li><li>
Contribute to hiring, onboarding, performance development, and team operating rhythms as the data engineering function grows</li></ul>
Cloud Platform &amp; Production Operations<ul><li>
Deploy, operate, and improve data pipelines, data stores, and supporting infrastructure on major cloud platforms such as AWS, GCP, or Azure</li><li>
Drive strong practices for CI/CD, infrastructure-as-code, automated testing, monitoring, alerting, and incident response</li><li>
Ensure data systems are observable, fault-tolerant, recoverable, and maintainable in production</li><li>
Identify opportunities to reduce operational toil, improve platform reliability, and manage cloud infrastructure costs effectively</li></ul>
Data Quality, Governance &amp; Trust<ul><li>
Define and enforce standards for data quality, validation, reconciliation, lineage, schema evolution, metadata, and documentation</li><li>
Establish patterns for data contracts, ownership, SLAs, and runbooks that help downstream teams trust and use data confidently</li><li>
Partner with security, compliance, and business stakeholders to support privacy, auditability, access controls, and regulated data handling</li><li>
Raise the maturity of data governance and reliability practices without slowing down pragmatic delivery</li></ul>
Cross-Functional Partnership<ul><li>
Partner closely with Product, Engineering, AI, Analytics, and business stakeholders to align data architecture with organizational priorities</li><li>
Translate ambiguous business needs and operational workflows into clear technical plans, milestones, and production-ready solutions</li><li>
Serve as a senior technical point of contact for data-heavy initiatives, communicating tradeoffs, risks, sequencing, and timelines clearly</li><li>
Enable downstream consumers, including analysts, product teams, data scientists, and operational users, through reliable and well-modeled data assets</li></ul>
Culture &amp; Craft<ul><li>
Contribute to a culture of ownership, curiosity, operational rigor, pragmatism, and engineering excellence</li><li>
Raise the bar for the team through thoughtful design, clear abstractions, strong reviews, and sound technical judgment</li><li>
Balance staff-level technical depth with practical people leadership, helping the team grow while continuing to ship high-quality systems</li></ul>
Qualifications:
<ul><li>5-8+ years of experience building and operating production-grade data pipelines, platforms, and distributed data systems</li><li>
2+ years of experience leading, mentoring, or managing data engineers in a tech lead, staff-level project lead, engineering manager, or TLM capacity</li><li>
Strong hands-on experience with industry-standard tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI</li><li>
Deep understanding of OLTP and OLAP systems, including the ability to design architectures that support transactional, analytical, and operational workloads</li><li>
Experience building flexible data pipelines across many source and destination types, including databases, APIs, files, queues, event streams, SaaS platforms, and internal systems</li><li>
Strong experience with both batch and real-time processing patterns, including tradeoffs in latency, reliability, cost, and operational complexity</li><li>
Experience deploying and operating cloud-based data infrastructure on AWS, GCP, or Azure</li><li>
Advanced SQL and data modeling expertise, including schema design, warehouse optimization, semantic modeling, and performance tuning</li><li>
Strong programming ability in languages commonly used in data engineering, such as Python, Java, Scala, Go, or similar</li><li>
Comfort with CI/CD, infrastructure-as-code, automated testing, observability, incident response, and production operations for data systems</li><li>
Strong architectural judgment in ambiguous environments where systems must balance speed, reliability, compliance, maintainability, and long-term leverage</li><li>
Clear communication skills with both technical and non-technical teammates, including the ability to explain tradeoffs and influence direction</li></ul><div></div> 
Preferred Experience<ul><li>
Experience operating as a Technical Lead or Tech Lead Manager responsible for both technical implementation, technical direction, and people development</li><li>
Experience with modern orchestration and transformation tools such as Airflow, Dagster, dbt, or similar platforms</li><li>
Experience with cloud-native warehouses or lakehouse platforms such as Snowflake, BigQuery, Redshift, Databricks, or equivalent technologies</li><li>
Experience with streaming systems such as Kafka, Kinesis, Pub/Sub, Flink, Spark Streaming, or similar technologies</li><li>
Experience enabling BI and self-service analytics through curated datasets, semantic layers, and reporting platforms such as Looker, Tableau, Power BI, or similar tools</li><li>
Experience building data platforms that support AI, machine learning, decisioning, or LLM-powered workflows</li><li>
Experience scaling a data engineering function, including technical standards, operating rhythms, hiring, onboarding, and team development</li><li>
Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains</li></ul> 
A Note to Candidates<div>
You do not need prior fintech or finance experience to succeed in this role. If you are a senior data engineer with strong architectural judgment, a hands-on builder mindset, and the ability to develop other engineers, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply.</div><div></div><div> 
Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.</div><div></div><div> 
#LI-Remote</div></div>

Lead Data Engineer

H2o Labs

Senior / Lead / Data Engineer &ndash; Comprehensive Job DescriptionAbout the RoleWe are seeking a highly skilled and experienced Senior/Lead/Staff Data Engineer todesign, build, and maintain scalable, reliable, and high-performance data systems. Thisrole requires deep technical expertise, strong ownership of data platforms, and the abilityto lead cross-functional initiatives that power analytics, machine learning, businessintelligence, and mission-critical applications.You will play a key role in shaping data architecture, ensuring data quality and governance,and enabling teams across the organization to make data-driven decisions withconfidence.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models, including:</li></ul>o Star schema (fact and dimension tables)o Conceptual, logical, and physical data models<ul><li>Develop enterprise data warehouse solutions ensuring:</li></ul>o Flexibility, scalability, and performance optimization<ul><li>Define and enforce data modeling standards and best practices</li></ul>Data Engineering &amp; Pipeline Development<ul><li>Build and maintain end-to-end data pipelines:</li></ul>o Data ingestion &rarr; staging &rarr; transformation &rarr; serving layers<ul><li>Develop robust ETL/ELT processes using modern tools and frameworks</li><li>Implement:</li></ul>o Typed staging layerso Data validation pipelineso Safe backfill and replay mechanisms<ul><li>Optimize SQL queries, indexing strategies, and database performanceData Platform Reliability &amp; Observability</li><li>Own data pipeline reliability and integrity</li><li>Build observability systems, including:</li></ul>o Monitoring dashboardso Alerting frameworks (actionable, low-noise)o Data freshness tracking<ul><li>Implement:</li></ul>o Schema contracts and enforcemento Data quality checks and validation ruleso Failure detection in CI pipelines (not post-deployment)<ul><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks:</li></ul>o Standards, policies, and best practices<ul><li>Enforce:</li></ul>o Data integrityo Data lineage and traceabilityo Access controls and compliance<ul><li>Separate and maintain clear boundaries between:</li></ul>o Core governed datasetso Downstream analytics/BI layersCloud &amp; Big Data Integration<ul><li>Integrate systems with:</li></ul>o Data lakes and large-scale data platforms<ul><li>Work with modern cloud ecosystems (AWS preferred):</li></ul>oo Data warehouse platforms (e.g., Redshift, Snowflake)<ul><li>Design cost-efficient and scalable data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Design and deliver data products used by:</li></ul>o Analystso Data scientistso Product teams<ul><li>Build reusable frameworks for:</li></ul>o Data transformationo Orchestrationo Feature engineering (ML readiness)<ul><li>Support advanced analytics and reporting use cases</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate:</li></ul>o Testingo Deploymento Validation<ul><li>Use version control systems (Git/GitHub)</li><li>Ensure:</li></ul>o High availabilityo Backup and recovery strategiesProgramming &amp; Tooling<ul><li>Develop solutions using:</li></ul>oo Python (automation, validation, tooling)<ul><li>Work with tools such as:</li></ul>o dbt (deep experience required)o DBeaver, Visual Studioo Orchestration tools (e.g., Dagster or similar)Leadership &amp; Collaboration<ul><li>Lead cross-functional technical initiatives</li><li>Mentor and guide junior to mid-level data engineers</li><li>Conduct:</li></ul>o Code reviewso Architecture discussionso Knowledge sharing sessions<ul><li>Collaborate with:</li></ul>o Engineering teamso Product managerso Business stakeholders<ul><li>Translate business requirements into scalable data solutions</li></ul>Strategic Impact<ul><li>Drive platform evolution and innovation</li><li>Identify opportunities for:</li></ul>o Performance improvementso Cost optimization (FinOps mindset)o Automation and scalability<ul><li>Influence organizational data strategy and roadmapRequired Qualifications</li><li>Bachelor&rsquo;s degree in computer science, Engineering, IT, or related field</li><li>4&ndash;5+ years of experience in data engineering or analytics engineering</li><li>Strong expertise in:</li></ul>o Data modeling (star schema, dimensional modeling)o SQL and performance tuningo ETL/ELT pipeline development<ul><li>Hands-on experience with:</li></ul>o Data warehousing and data lakeso Big data integrations<ul><li>Experience with:</li></ul>o Cloud platforms (AWS preferred)o Data quality, validation, and governance frameworks<ul><li>Strong understanding of:</li></ul>o System designo Scalable architecture<ul><li>Excellent communication and stakeholder management skills</li><li>Ability to work in agile, fast-paced environments</li><li>Eligibility to obtain security clearance (if required)</li></ul>Preferred Qualifications<ul><li>Experience with:</li></ul>o AWS services (Glue, Lambda, etc.)o Snowflake, Redshifto dbt (production-level deployments)<ul><li>Knowledge of:</li></ul>o Machine learning data pipelineso Certifications:o SQL Server, CDMP, MCSA, or similar<ul><li>Experience in:</li></ul>o Healthcare, defense, or regulated industries<ul><li>Familiarity with:</li></ul>o CI/CD for data systemso Data governance and FinOps practicesWhat Makes a Strong Candidate<ul><li>Thinks of systems, not just pipelines</li><li>Focuses on root-cause solutions, not temporary fixes</li><li>Balances:</li></ul>o Business valueo Scalabilityo Maintainability<ul><li>Strong ownership mindset with ability to lead initiatives end-to-end</li><li>Passion for building resilient, high-quality data platforms</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs350,000.00 per monthWork Location: In person

Envestnet

<div>Description
Job Location
The primary work location for this role is Raleigh, NC with a hybrid work model. 
About Envestnet
Envestnet is an adaptive WealthTech company that is redefining the future of wealth management by helping advisors meet the moment with its comprehensive technology, actionable insights, and industry leading support. Backed by over 25 years of experience and approximately $7.0 trillion in platform assets, Envestnet is trusted by over one third of financial advisors across leading banks, wealth managers, brokerages, and RIAs. 
For a deeper look at how Envestnet is shaping the future of financial advice, visit www.envestnet.com. 
The Team You&rsquo;ll Join
The Lead Data Engineer will play a critical implementation role on the Data Engineering and Data Services team and be responsible for data pipeline solutions design and development, troubleshooting, and optimization tuning on the next generation data and analytics platform being developed with leading edge big data technologies in a highly secure cloud infrastructure. The Data Engineer will serve as a liaison to platform user groups ensuring successful implementation of capabilities on the new platform. The Lead Data Engineer will also take a lead role on functional teams or projects. 
How You&rsquo;ll Contribute 
<ul><li>
Deliver end-to-end data and analytics capabilities, including data ingest, data transformation, data science, and data visualization in collaboration with Data and Analytics stakeholder groups.</li><li>
Design and deploy databases and data pipelines to support analytics projects.</li><li>
Develop scalable and fault-tolerant workflows.</li><li>
Clearly document issues, solutions, findings and recommendations to be shared internally &amp; externally.</li><li>
Learn and apply tools and technologies proficiently, including:</li><li>
Languages: SQL (standard and DB-specific), Python, Scala, Bash</li><li>
Frameworks: Hadoop, Spark, Kafka</li><li>
Gen AI: RAG, Embedding, Agents, LLMs, Parameter Tuning</li><li>
Cloud Computing: AWS</li><li>
Tools/Products: Data Science Studio, Alteryx, Jupyter, Tableau, PowerBI</li><li>
Performance optimization for queries and dashboards.</li><li>
Develop and deliver clear, compelling briefings to internal and external stakeholders on findings, recommendations, and solutions.</li><li>
Analyze client data &amp; systems to determine whether requirements can be met.</li><li>
Test and validate data pipelines, transformations, datasets, reports, and dashboards built by team.</li><li>
Develop and communicate solutions architectures and present solutions to both business and technical stakeholders.</li><li>
Provide end user support to other data engineers and analysts.</li><li>
Be a team leader and take lead role on functional teams or projects.</li><li>
Leads others to solve complex problems; uses sophisticated analytical thought to exercise judgment and identify innovative solutions.</li><li>
Interprets internal/external business challenges and recommends best practices to improve products, processes or services.</li><li>
Adherence to and application of Envestnet legal, compliance, risk, business continuity and administrative policy within the role and department(s) including the timely completion of training &amp; awareness, affirmations and testing as requested.</li><li>
As part of the responsibilities for this role, you will understand and readily support Envestnet's established corporate business practices, policies, internal controls and procedures designed to create value or minimize risk.</li></ul> 
What You&rsquo;ll Need to Bring 
<ul><li>
8-12 years of relevant experience or equivalent combination of experience and education.</li><li>
Expert experience in the following:</li><li>
SQL, Python, PySpark. Other programming languages (R, Scala, SAS, Java, etc.) are a plus.</li><li>
Data and analytics technologies including SQL/NoSQL/Graph databases, ETL, and BI.</li><li>
Knowledge of CI/CD and related tools such as Gitlab, AWS CodeCommit, etc.</li><li>
AWS services including EMR, Glue, Athena, Batch, Lambda Cloudwatch, DynamoDB, EC2, Cloudformation, IAM and EDS.</li><li>
Solid scripting skills (e.g., bash/shell scripts, Python).</li><li>
Proven work experience in the following:</li><li>
Data streaming technologies</li><li>
Using LLMs, creating RAG, choosing vector vs graph db for embedding, etc.</li><li>
Big Data technologies including, Hadoop, Spark, Hive, Teradata, etc.</li><li>
Linux command-line operations.</li><li>
Networking knowledge (OSI network layers, TCP/IP, virtualization).</li><li>
Candidate should be able to lead the team, communicate with business, gather and interpret business requirements.</li><li>
Experience with agile delivery methodologies using Jira or similar tools.</li><li>
Experience working with remote teams</li></ul> 
Nice-to-Haves 
<ul><li>
AWS Solutions Architect / Developer / Data Analytics Specialty certifications, Professional certification is a plus.</li><li>
Bachelor Degree in Computer Science or relevant field, Masters Degree is a plus.</li></ul> 
Why You&rsquo;ll Enjoy Working at Envestnet
Help shape the future of WealthTech. At Envestnet you&rsquo;ll gain hands-on experience and collaborate with some of the industry&rsquo;s brightest minds to deliver meaningful, innovative solutions that make a real difference. 
We value flexibility in how and where work gets done, and we recognize strong performance with meaningful rewards&mdash;because your contributions should drive both business success and your own personal growth. If you&rsquo;re looking for a place where your work has impact, your development is supported, and your contributions are truly valued, Envestnet is where you can build your future. 
The opportunity is now! 
Sponsorship
This position is not open to candidates requiring visa sponsorship 
Our Investment in You
At Envestnet, our total rewards philosophy is designed to attract, motivate, and grow exceptional talent. We offer competitive, market-aligned compensation complemented with performance-linked incentives and rewards programs that recognize and reward impact. 
We provide a comprehensive suite of benefits - subject to Envestnet&rsquo;s plan eligibility rules - that support your overall well-being including, medical insurance, paid time off (PTO), 401k company match, paid parental leave, education reimbursement, disability coverage and mental health &amp; wellness support. Our investment in you means supporting you professionally, financially, and personally at every stage of your journey with us. Please visit our benefits page on our career site to learn more. 
Our Commitment to Inclusion &amp; Belonging
Envestnet is an Equal Opportunity Employer and is committed to creating an inclusive environment for all employees and applicants. We welcome and value individuals of all backgrounds and do not discriminate based on race, color, religion, creed, sex (including pregnancy or related medical conditions), gender identity or expression, sexual orientation, national origin, ancestry, age, disability, genetic information, military or veteran status, citizenship status, or any other status protected by applicable law. We encourage individuals from all backgrounds to apply. 
We strive to provide an inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation, please contact us at careers@envestnet.com. Please include your full name, the title of the role you are applying for, and the accommodation necessary to assist you with the recruiting process. 
Recruitment Fraud
At Envestnet, safeguarding the trust and safety of job seekers is a top priority. We are aware that scammers may impersonate Envestnet recruiters or create fake job opportunities to deceive candidates. Review the information on our recruitment fraud awareness page to help you recognize and avoid recruitment fraud.
#LI-AQ1 #LI-REMOTE</div>

RedCloud Technologies

<div>Lead Data Engineer
About RedCloud
The global supply chain is broken&mdash;creating a $2 trillion inventory gap where essential consumer goods fail to reach the people who need them. Brands miss sales, distributors mismanage stock, and retailers face empty shelves. The result? Higher prices, slower growth, and lost opportunity across the board.
RedCloud is fixing this. Our RedAI digital trading platform, bulk and retail trading exchanges connect key parts of the supply chain&mdash;enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment&mdash;facilitating smarter everyday business decisions for our customers, from factory to warehouse to store.
Headquartered in London, RedCloud became a publicly listed company on Nasdaq (RCT) in March 2025. With a diverse team spanning many nationalities and operations across Africa, the Middle East, Europe, and Latin America. We&rsquo;re building a more connected and efficient global trade network. Our AI labs are busy exploring the next generation of smart AI agents and deeper FMCG market intelligence for the benefit of our customers across a growing operational footprint.
The role:
A Lead Data Engineer builds, maintains and supports our data warehouse, delivering data to the whole business in an easy, performant and readable format. They are the core engineers that empower the data behind our AI strategies and business decisions. They will work in a squad along side data scientists and AI engineers allowing for a whole picture on how the data is used. The ideal candidate will have Technical skills across SQL, Database Design (snowflake, PostgreSQL, MySQL) and Python.
What will you be doing:
Architect Data Warehouse
Own the architecture and flow of data into our data warehouse through collaboration with the squad, other squads and the wider business. Partner with the product manager to support and deliver a data warehouse that is performant, readable, easy to use and enables the business needs of other teams.
Design, Build and Maintain ELT Solutions
Design, build and maintain systems to consume data from other Internal RedCloud Systems and External Partners and/or Customers.
Deliver Data Insights
Work with colleagues through the business and directly with customers helping them to understand the data we have, build and refine models to help them deliver impact, carry out change or drive additional revenue through our customer base.
Resolve Bugs
Investigate and resolve bugs in our systems.
Handle production Outages / issues
Respond to production outages and issues in our systems.
Estimate Features / Bugs
Estimate features and bugs within estimation sessions alongside the team.
Refine feature requirements
Refine features delivered by product managers.
Carry out code reviews
Carry out code reviews / Pull-request reviews for other engineers, ensuring quality on code.
Keeping pace with Technology
As a senior member of the squad train and learn latest technologies adopted by RedCloud suggesting future libraries and patterns we should be looking at as a business.
Soft Skills
Mentor Members of the Team
Mentor all levels of engineers and new starters in the team, as their RedCloud buddy. Ensure they have all they need to succeed within your team.
Communication
Communicate effectively and clearly to those within your team and across the business.
Even if you feel you don&rsquo;t meet every requirement above, we still strongly encourage you to apply. Your unique experiences, qualities and perspectives might be just what we&rsquo;re looking for.
Benefits
Working with a pioneering trading, data and Intelligence company in the FMCG industry you will have the opportunity to join an international organisation tipped to grow fast - we encourage and reward ambition, creativity and the ability to thrive in this environment.
The successful candidate will get:<ul><li>25 Days Annual leave, increasing to 26 days after 12 months in the business</li><li>Enhanced Company Pension (Matched up to 5% &amp; Salary Sacrifice)</li><li>Healthcare Cashplan with Medicash</li><li>Private Healthcare with Aviva</li><li>Life Insurance with AIG</li><li>Happl, our benefit platform which provides access to pre-negotiated discounts on a wide variety of services including entertainment, food, and fitness.</li><li>Stock / Equity (new scheme being established post IPO)</li></ul>
Check out the links below to see what our CEO Justin Floyd has to say about our plans for growth for the year ahead, and to see our latest video on the mission we&rsquo;re on!
https://youtu.be/8BmLoJ9U9vA
https://youtu.be/59PD4UoTgIE</div>

PetroApp

<div>About the role
We are looking for a highly capable, hands-on Data Lead to build and scale PetroApp&rsquo;s data function.
This role will own the end-to-end data roadmap across analytics, business intelligence, data engineering, governance, and advanced analytics use cases. You will work closely with Product, Engineering, Operations, Commercial, Finance, and Leadership to make data a core competitive advantage for PetroApp.
You will be responsible for building a trusted data foundation, defining the right KPIs, improving decision-making across the company, and enabling high-impact use cases such as transaction analytics, customer growth, fraud/anomaly detection, operational efficiency, and unit economics.
Key responsibilities<ul><li>
Define and own PetroApp&rsquo;s data strategy, roadmap, and operating model.</li><li>
Build and scale the company&rsquo;s data foundation, including ingestion, transformation, modeling, warehousing, and self-service analytics.</li><li>
Create a single source of truth for key business and product metrics.</li><li>
Partner with Product and Engineering to improve instrumentation, event tracking, experimentation, and measurement.</li><li>
Partner with Commercial, Operations, Finance, and Leadership to deliver actionable insights and decision-ready dashboards.</li><li>
Design KPI frameworks for areas such as customer growth, retention, transaction performance, service adoption, operational efficiency, fraud/leakage, and profitability.</li><li>
Build dashboards, reporting layers, and analytical models that support both day-to-day execution and executive decision-making.</li><li>
Establish strong data governance practices, including data quality checks, lineage, documentation, definitions, access controls, and privacy standards.</li><li>
Identify and prioritize high-value use cases for advanced analytics, forecasting, anomaly detection, and automation.</li><li>
Lead root-cause analysis on business or operational issues and convert findings into measurable actions.</li><li>
Hire, mentor, and grow a lean, high-performing data team over time.</li><li>
Act as the internal champion for a strong data culture across PetroApp.</li></ul> 

Requirements 
<ul><li>
10+ years of experience across data analytics, business intelligence, analytics engineering, data engineering, or related fields.</li><li>
2+ years leading major data initiatives, squads, or teams.</li><li>
Strong hands-on expertise in SQL and Python.</li><li>
Experience with modern cloud data stacks and tools such as data warehouses, ETL/ELT pipelines, orchestration tools, transformation frameworks, and BI platforms.</li><li>
Strong experience designing dashboards and reporting for business and executive stakeholders.</li><li>
Proven ability to define KPIs, create semantic consistency, and translate ambiguous business questions into structured analysis.</li><li>
Strong understanding of data modeling, pipeline design, and analytics best practices.</li><li>
Experience working in high-growth environments with cross-functional stakeholders.</li><li>
Excellent communication skills with the ability to influence both technical and non-technical audiences.</li>
Strong ownership mindset and willingness to operate hands-on. 
<li>
</li></ul>
Preferred experience<ul><li>
Experience in SaaS, fintech, payments, mobility, logistics, fleet management, marketplaces, or other transaction-heavy businesses.</li><li>
Experience with fraud analytics, anomaly detection, risk analytics, or reconciliation-heavy environments.</li><li>
Experience building data capabilities in a scaling company, including hiring and team design.</li><li>
Familiarity with experimentation, forecasting, segmentation, and behavioral analytics.</li><li>
Exposure to data governance, privacy, and access management in regulated or sensitive environments.</li></ul>
Why join this role
This is an opportunity to build the data function at the center of a scaling business. The Data Lead will shape how PetroApp measures performance, prioritizes opportunities, reduces leakage, improves customer outcomes, and scales intelligently. 
Benefits 
<ul><li>
You will own and shape the security function in a high-impact, hands-on lead role.</li><li>
You&rsquo;ll work at the intersection of security, reliability, and platform engineering, directly influencing how PetroApp scales.</li><li>
Opportunity to work with a modern tech stack and a team that values pragmatism, automation, and continuous improvement.</li><li>
A culture that cares about doing the right thing for customers and partners, with leadership support for investing in security and reliability.</li></ul></div>

Capgemini

<div><div><div><div>Job Description
We are seeking a skilled Data Engineer with hands-on experience in Databricks and Google Cloud Platform (GCP) to design, build, and optimize data pipelines and analytics solutions. The ideal candidate will have a strong background in distributed data processing, cloud architecture, and data modeling. This role partners closely with data analysts, data scientists, and business stakeholders to deliver scalable, reliable, and high‑quality data products.
Your role
Design, build, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake).
 
Optimize pipelines for performance, cost efficiency, and scalability within GCP.
 
Develop batch and streaming data processes using Spark Streaming, and related technologies.
 
Implement data solutions leveraging GCP services such as BigQuery, Cloud Storage, Dataflow, Cloud Composer, and Vertex AI integrations.
 
Apply best practices for cloud security, IAM configuration, monitoring, and cost management.
 
Build and maintain data models, including dimensional modeling and data vault structures.
 
Implement data quality frameworks, validation rules, and automated testing.
 
Manage data versioning, governance, and lineage using tools such as Unity Catalog or GCP Data Catalog.
 
Partner with cross‑functional teams to gather requirements and translate them into technical designs.
 
Provide technical guidance and influence engineering best practices across the team.
 
Contribute to documentation, architectural diagrams, and knowledge sharing.
Your Skills and Experience
Required
 
Experience as a Data Engineer or similar role.
 
Strong hands-on experience with Databricks, including:
 
PySpark/Spark
 
Delta Lake
 
Databricks workflows/jobs
 
Proficiency with GCP:
 
BigQuery
 
Cloud Storage
 
Dataflow or Dataproc
 
Strong coding skills in Python and SQL.
 
Solid understanding of distributed systems, data warehousing, and data architecture principles.
 
Experience with CI/CD tools (GitHub, GitLab, Azure DevOps, or similar).
Preferred Qualifications
Databricks or GCP certifications (e.g., Data Engineer, Architect).
 
Experience with Terraform or other Infrastructure-as-Code tools.
 
Knowledge of ML workflows or MLOps frameworks.
 
Familiarity with data governance tools (Unity Catalog, Great Expectations, dbt, etc.).
<div><div><div><h2 class="jobSectionHeader">Job Description</h2>
</div><div>Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.</div>
</div><div><div><h2 class="jobSectionHeader">Job Description - Grade Specific</h2>
</div><div>The role involves leading and managing a team of data engineers, defining and executing the data engineering strategy, and ensuring the effective delivery of data solutions. They provide technical expertise, drive innovation, and collaborate with stakeholders to deliver high quality, scalable, and reliable data infrastructure and solutions.</div>
</div></div>The base compensation range for this role in the posted location is $76,200 to $187,740
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. 
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul>Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. 
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law 
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</div></div></div></div>

GCP Lead Data Engineer

JPMorganChase

<div>JOB DESCRIPTION 
Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.
As a Lead Data Engineer at JPMorganChase within the Commercial &amp; Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm&rsquo;s business objectives.
Job responsibilities<ul><li>
Design, build, and maintain scalable, high-performance data pipelines and infrastructure to support ingestion, processing, and storage of large volumes of scanned document images across enterprise-wide workflows</li><li>
Architect end-to-end data solutions on AWS cloud services to enable seamless flow of scanned images from source systems through OCR processing, model inference, and downstream data extraction and categorization pipelines</li><li>
Develop robust image preprocessing and OCR integration pipelines that handle TIF/PNG format conversion, normalization, resolution enhancement, noise reduction, and batching to prepare scanned documents for downstream computer vision and OCR models</li><li>
Build and optimize data pipelines that integrate OCR engine outputs, extracting structured text and metadata from scanned images and routing them into databases and analytics platforms for further processing</li><li>
Design and manage data storage architectures and containerized deployments, using Oracle databases and AWS-native stores (S3, EFS) to efficiently catalog, index, and retrieve extracted text, classification labels, and metadata from processed document images</li><li>
Drive the adoption of containerized deployment strategies using AWS EKS (Elastic Kubernetes Service) to deploy and scale image processing microservices, OCR engines, and data pipeline components with high availability and fault tolerance</li><li>
Collaborate closely with data scientists and ML engineers to ensure training datasets for different models, and other computer vision models are properly curated, versioned, labeled, and accessible through well-structured data pipelines
</li><li>Evaluate and integrate emerging data technologies and tools to continuously improve pipeline throughput, reduce processing latency for high-volume document scanning workloads, and optimize cost efficiency</li><li>
Establish and enforce data quality, lineage, governance, and security frameworks to ensure traceability and integrity of extracted data from scanned documents throughout the entire processing lifecycle</li><li>
Partner with security and compliance teams to ensure that scanned document data, extracted PII/PHI, and sensitive content are handled in accordance with regulatory requirements, encryption standards, and access controls</li><li>
Lead and mentor a team of data engineers, establishing coding standards, peer review processes, CI/CD workflows, and best practices for building production-grade image and document processing pipelines</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on Data Engineering concepts and 5+ years applied experience</li><li>
Strong proficiency in Java, Groovy, and Python for building data pipelines, image preprocessing workflows, automation scripts, and backend data services</li><li>
Hands-on experience with image file handling, particularly TIF/PNG format processing, multi-page document splitting, format conversion, and integration with OCR and computer vision pipelines</li><li>
Deep hands-on experience with AWS cloud services including S3 (for image storage), Lambda, Step Functions, and CloudWatch for building and monitoring scalable data workflows</li><li>
Expertise in AWS EKS (Elastic Kubernetes Service) for deploying and managing containerized image processing, OCR, and data pipeline services using Docker and Kubernetes</li><li>
Advanced knowledge of Oracle databases including PL/SQL, performance tuning, partitioning strategies, and data modeling for storing and querying large volumes of extracted document data and classification results</li><li>
Familiarity with OCR technologies and the ability to build data pipelines that consume and structure OCR output for downstream analytics and model training</li><li>
Understanding of data requirements for training deep learning models including dataset preparation, annotation management, and feature store integration</li><li>
Experience with CI/CD pipelines (Jenkins) and infrastructure-as-code tools (Terraform, CloudFormation) for automated deployment and environment management</li><li>
Strong understanding of data governance, data quality frameworks, metadata management, and data cataloging, particularly in the context of document-centric and image-heavy data ecosystems</li><li>
Excellent leadership, communication, and stakeholder management skills with the ability to drive technical decisions across cross-functional teams</li></ul><div>
</div><div>Preferred qualifications, capabilities, and skills</div><div>
</div><ul><li>Domain expertise in the healthcare industry</li></ul>
ABOUT US 
<div>
<div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
<div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM 
 
J.P. Morgan&rsquo;s Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

AI/ML Lead Data Engineer - Automation/Image Processing

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