data engineering manager

Ford Motor Company

<div>As a Senior Data Engineering Manager, you will lead a team responsible for the strategic development and delivery of data products. You will oversee the integration of data from various sources, guiding the evolution of our analytical data landscape, including the merging of historical data from legacy platforms with data ingested from new platforms. Your role involves directing the analysis and manipulation of large datasets, ensuring the activation of data assets to enable enterprise platforms and analytics within Google Cloud Platform. You will also lead the design and implementation of data transformation and modernization initiatives on Google Cloud Platform, ensuring the creation of scalable data pipelines that land data from source applications, integrate into subject areas, and build data marts and products for analytics solutions.
You will guide your team in conducting deep-dive analyses, including those related to Current State Receivables and Originations data within our data warehouse, performing impact analysis related to Ford Credit North America's modernization efforts and providing strategic implementation solutions. This role requires significant experience supporting North American teams. Moreover, you will lead cross-functional efforts, partnering closely with our AI, data science, and product teams to develop innovative data solutions that build the future for Ford Credit. You will coach and mentor your direct reports, fostering professional growth and technical expertise. You will also work directly with the Director of Data Engineering, based in the United States, collaborating on strategic direction and execution.
We require demonstrated leadership in designing, implementing, and operationalizing large-scale data warehouses, data lakes, and analytics platforms on Google Cloud Platform or other cloud environments. We are looking for candidates with a proven ability to lead and guide a team of data engineers, drive technical architecture decisions, and make strategic technology choices within the Google Cloud Platform ecosystem and related third-party technologies. This includes demonstrating an ability to design the right solutions with the appropriate combination of technologies for deployment on Google Cloud Platform.</div>
 <div>Must Have Skills &ndash;
<ul><li>12+ years of technical leadership experience in delivery of Data Warehouse Solutions on-prem or on cloud for large companies, and business adoption of these platforms to build insights &amp; analytics
</li></ul><ul><li>8+ years&rsquo; experience leading technical teams, delivering complex projects using Agile methodologies, and product support for those solutions.
</li></ul><ul><li>Solid knowledge of cloud data architecture, data modelling principles, DevOps, Data compliance, global (North America/Europe) data protection laws, security and data governance.
</li></ul><ul><li>Very strong leadership and communication skills to aid customer and program teams in making data-driven decisions.
</li></ul><ul><li>Demonstrated experience required in engineering Data warehouse solution in Google or other cloud systems.
</li></ul><ul><li>Driven and managing complex projects &amp; aggressive timelines
</li></ul><ul><li>Google Cloud certified professional Data Engineer
</li></ul><ul><li>Bachelor&rsquo;s degree in- Computer science, Computer engineering, Data science or related field
</li></ul><ul><li>Experience on Google cloud with deep understanding and design and development experience with Google Cloud Platform products on Infrastructure, Data management, Application Development, Smart Analytics, Artificial Intelligence, Security and DevOps
</li></ul><ul><li>Knowledge of most of the following:
</li></ul>o Extract, Transform and Load (ETL) &amp; Big Data Tools: BigQuery, Cloud Dataflow, Cloud Proc, Cloud Pub/Sub, Cloud Composer, Dataform, Data Plex, Google Looker Studio, Google Cloud Storage.
o Data Quality and Governance
o Designing, building, and deploying ML pipelines (MLOps) to solve business challenges using Python/BQML/Vertex AI on GCP. Work closely with data scientists to help deploy their models.
<ul><li>Proven track of managing large global budgets, and organization change management.
</li></ul><ul><li>Ability to negotiate with and influence stakeholders &amp; drive forward strategic data transformation
</li></ul><ul><li>Quick learner, self-starter, energetic leaders with drive to deliver results.
</li></ul><ul><li>Empathy and care for customers and teams, as a leader guide teams on advancement of skills, objective setting and performance assessments. 
</li></ul>Good to Have Skills &ndash;
<ul><li>Master of Business Administration (MBA)
</li></ul><ul><li>Experience in technical program management &amp; delivering transformational projects
</li></ul><ul><li>Building high performance teams
</li></ul><ul><li>Managing/or working with globally distributed teams
</li></ul><ul><li>Prior experience in leveraging offshore development service providers
</li></ul><ul><li>Experience in a Fintech/Banking or large manufacturing company.</li></ul></div>
 <div><ul><li>Accountable for supporting the creation of the modern Datawarehouse platform in Google Cloud that enables Analytics, insights &amp; AI/ML at speed.
</li></ul><ul><li>Managing stakeholders and projects, collaborating on prioritization strategies, roadmaps, architecture &amp; features delivery
</li></ul><ul><li>Leading enablement of new GCP BQ capabilities &amp; engineering patterns for enterprise-wide adoption.
</li></ul><ul><li>Accountable for ensuring data solutions pass banking regulatory and compliance standards.
</li></ul><ul><li>Provide technical leadership in design &amp; delivery of Google cloud data platform, using agile practices and delivering continuous business value
</li></ul><ul><li>Drive business adoption of new scalable and reliable data platform for enterprise&rsquo;s data analytics, Insights &amp; AI/ML modeling requirements
</li></ul><ul><li>Collaborate with Architects and cross functional application/product teams and Ford Data Factory team to integrate data solutions required to support multiple parallel projects
</li></ul><ul><li>Familiarity with hands-on development of reusable solution patterns with advanced GCP tools &amp; guide teams on how to effectively use these tools
</li></ul><ul><li>Be the trusted partner of business customers and engineering teams in solving technical and business problems.
</li></ul><ul><li>Effectively manage team&rsquo;s priorities, backlogs and help remove roadblocks, to drive key business results
</li></ul><ul><li>Lead communication of status, issues &amp; risks to key stakeholders
</li></ul><ul><li>Stay abreast on technology advancements and ensure team keeps updated on skills
</li></ul>&middot; Experience leading large team of data engineers &amp; developing talent, performance management. &middot; Drive adoption of standardized architecture, design and quality assurance approaches across all workstreams and ensure solutions adhere to established standards.
<ul><li>Leverage cloud AI/ML Platforms to deliver business and technical requirements. Manage data engineers and ML engineers that work with teams of data scientists, data analysts, and architects to successfully deliver ML/AI projects.</li></ul></div>

Senior Data Engineering Manager

Optum

<div>Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. 
We are seeking a highly skilled and proactive Data Engineer with 7+ years of experience in designing and building scalable data solutions across cloud platforms. This role demands deep expertise in Databricks, data pipeline architecture, and hands-on leadership in engineering teams. The ideal candidate will be instrumental in driving the development of robust data pipelines, mentoring junior engineers, and coordinating cross-functional efforts to deliver high-quality data products in the healthcare domain. 
Primary Responsibilities:<ul><li>
Design, develop, and optimization of data pipelines using Databricks (PySpark, SQL) across Azure and GCP environments</li><li>
Architect and manage Snowflake and BigQuery data warehouse solutions for performance, scalability, and cost-efficiency</li><li>
Collaborate closely with stakeholders to understand data requirements and translate them into technical solutions</li><li>
Perform advanced data analysis on healthcare datasets (claims, EMR, HL7, FHIR) to support strategic decision-making</li><li>
Drive hands-on coordination of engineering tasks, ensuring timely delivery and quality standards</li><li>
Mentor and guide junior data engineers, fostering best practices in coding, testing, and documentation</li><li>
Implement and maintain data governance, lineage, and security using tools like Unity Catalog, Terraform, and GitLab CI/CD</li><li>
Ensure compliance with healthcare data regulations (HIPAA, HITRUST) and internal security policies</li><li>
Contribute to the evolution of data engineering standards, reusable frameworks, and automation strategies</li><li>
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so</li></ul>
Required Qualifications:<ul><li>
Skills &amp; Experience:<ul><li>
7+ years of experience in data engineering, with a solid focus on cloud-native data pipelines</li><li>
Expert-level proficiency in Databricks, PySpark, SQL, and data orchestration</li><li>
Proven experience with Snowflake, BigQuery, and healthcare data formats (FHIR, HL7, claims, EMR)</li><li>
Hands-on experience with CI/CD, DevOps for data, and infrastructure-as-code</li><li>
Solid understanding of Azure and GCP cloud services including Data Factory, Synapse, Cloud Composer, and Google Cloud Storage</li><li>
Proven excellent communication and leadership skills, with a track record of mentoring and team coordination</li></ul></li></ul> 
Preferred Qualifications:<ul><li>
Bachelor's or Master's degree in Computer Science, Engineering, or related field</li><li>
Certifications in Databricks, Snowflake, or GCP</li><li>
Experience with orchestration tools like Airflow, dbt, or Cloud Composer</li><li>
Experience working with healthcare payers, providers, or analytics teams</li></ul> 
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.</div>

Data Engineering Manager - Databricks, Snowflake - Healthcare Domain

Caterpillar

<div>Career Area:
Technology, Digital and Data
Job Description:
Your Work Shapes the World at Caterpillar Inc.
When you join Caterpillar, you're joining a global team who cares not just about the work we do &ndash; but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here &ndash; we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
We are seeking a highly skilled and visionary Software Engineering Manager to lead a team of engineers in building Caterpillar&rsquo;s next-generation Digital Manufacturing Data Platform. This platform is central to our Future of Manufacturing initiative&mdash;designed to unify and operationalize data across design, engineering, production, and supply chain operations.
The ideal candidate will possess deep expertise in Big Data, Data Warehousing, real-time data movement, and Snowflake-based architectures. You will architect and deliver scalable, secure, and intelligent data platforms that enable advanced analytics, AI, and digital twin capabilities across global manufacturing ecosystems.<div></div>
Key Responsibilities
Team Leadership &amp; Management<ul><li>
Lead, mentor, and manage a team of data engineers and platform developers.</li><li>
Foster a culture of technical excellence, collaboration, and continuous learning.</li><li>
Drive Agile practices and ensure timely delivery of high-quality solutions.</li></ul>
Technical Strategy &amp; Architecture<ul><li>
Architect and oversee the development of scalable, secure, and resilient data platforms.</li><li>
Design and implement near real-time data movement and streaming architectures using tools like Kafka, Spark, and cloud-native services.</li><li>
Establish best practices in data modeling, ETL/ELT, data governance, and metadata management.</li></ul>
Data Engineering &amp; Snowflake Expertise<ul><li>
Lead the development of robust data pipelines for ingestion, transformation, and delivery using Snowflake, dbt, and cloud-native tools.</li><li>
Optimize data storage, retrieval, and processing for performance, reliability, and cost-efficiency.</li><li>
Implement data quality frameworks, lineage tracking, and schema evolution strategies.</li></ul>
Big Data &amp; Data Warehousing<ul><li>
Build and maintain large-scale data lakes and data warehouses for structured and unstructured data.</li><li>
Design scalable data architectures to support manufacturing analytics, predictive maintenance, and supply chain optimization.</li></ul>
Cloud &amp; Platform Engineering<ul><li>
Leverage Azure and AWS services for data ingestion, transformation, and analytics.</li><li>
Deploy software using CI/CD tools (Azure DevOps preferred, Jenkins, AWS CloudFormation).</li><li>
Ensure platform scalability, security, and operational readiness across global deployments.</li></ul>
AI &amp; Advanced Analytics Enablement<ul><li>
Collaborate with Data Science and AI teams to operationalize ML models and analytics workflows.</li><li>
Promote integration of AI capabilities into data engineering pipelines (e.g., GenAI, MCP, ATA).</li><li>
Support real-time analytics and edge AI use cases in manufacturing environments.</li></ul>
Stakeholder Engagement<ul><li>
Partner with product managers, manufacturing SMEs, and business leaders to understand requirements and deliver impactful data solutions.</li><li>
Communicate technical concepts to non-technical audiences and influence strategic decisions.</li></ul><div></div>
Must-Have Skills<ul><li>
Proven experience in Big Data processing and Data Warehousing.</li><li>
Expertise in building end-to-end near real-time data pipelines for OLTP &amp; OLAP.</li><li>
Strong architecture exposure for building robust, scalable Data Platforms.</li><li>
Deep expertise in Snowflake, SQL, NoSQL, and distributed data systems.</li><li>
Experience with data transformation tools (dbt, Apache Spark, Azure Data Factory).</li><li>
Strong analytical skills and solid knowledge of computer science fundamentals.</li><li>
Deep exposure to Azure and AWS cloud platforms.</li><li>
Good understanding of AI concepts and latest developments (Gen AI, MCP, ATA, etc.).</li></ul><div></div>
Nice-to-Have Skills<ul><li>
Knowledge of the NVIDIA ecosystem and its applications in data and AI.</li><li>
Experience building production-ready AI solutions and integrating with MLOps workflows.</li><li>
Familiarity with modern data visualization and BI tools (e.g., Power BI, Tableau, Looker).</li></ul><div></div>
Qualifications<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or related field.</li><li>
15+ years of experience in data engineering, with at least 5+ years in a leadership role.</li><li>
Demonstrated success in managing engineering teams and delivering complex data solutions.</li><li>
Excellent communication, leadership, and stakeholder management skills.</li></ul>
Relocation is available for this position.
Posting Dates:
October 22, 2025 - October 30, 2025
Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply
Not ready to apply? Join our Talent Community.</div>

Senior Manager Software Engineering-Data Engineering

<div>Line of Service
Advisory
Industry/Sector
Technology
Specialism
Advisory - Other
Management Level
Manager
Job Description &amp; Summary
As a Data Engineering Manager, you will lead the design, development, and optimization of modern data platforms and pipelines on Azure and Databricks. You will oversee a team of data engineers and collaborate with cross-functional stakeholders to deliver scalable, secure, and high-performing data solutions that enable advanced analytics, AI, and business insights for enterprise clients.
 
This role requires deep expertise in cloud data architecture, hands-on experience with Azure data services (including Microsoft Fabric), and advanced proficiency in Databricks for batch and real-time data engineering. You will also be responsible for mentoring team members, driving technical excellence, and aligning data engineering initiatives with business strategy.
<h3 class="jobSectionHeader">Key Responsibilities
</h3><ul><li>Lead the end-to-end delivery of data engineering projects, ensuring alignment with business goals and technical standards.
</li><li>Architect and oversee the implementation of scalable data pipelines across structured, semi-structured, and unstructured data sources.
</li><li>Guide the adoption of best practices in data ingestion, transformation, and orchestration using Azure Data Factory, Synapse, and Microsoft Fabric.
</li><li>Drive performance optimization and scalability of ETL/ELT processes using Databricks (PySpark, SQL, Delta Lake).
</li><li>Establish and enforce data governance, quality, lineage, and observability frameworks.
</li><li>Collaborate with solution architects and business leaders to define modern data architectures and ensure compliance with security and privacy regulations.
</li><li>Facilitate technical workshops, stakeholder engagements, and roadmap planning sessions.
</li><li>Mentor and develop junior engineers, fostering a culture of innovation, accountability, and continuous learning.
</li></ul><h3 class="jobSectionHeader">Required Skills &amp; Experience
</h3><ul><li>7&ndash;10 years of experience in data engineering, with at least 3 years in a leadership or managerial role .
</li><li>Proven track record of delivering enterprise-grade data solutions in consulting or large-scale environments.
</li><li>Advanced hands-on experience with:
<ul><li>Azure Data Platform : Data Factory, Synapse Analytics, Azure Data Lake Storage, Microsoft Fabric, Event Hub/IoT Hub, Azure Functions.
</li><li>Databricks : PySpark, Spark SQL, Delta Lake, Unity Catalog, Databricks Workflows.
</li></ul></li><li>Strong proficiency in Python and SQL for large-scale data processing.
</li><li>Expertise in data modeling, medallion architecture, and lakehouse principles.
</li><li>Familiarity with CI/CD pipelines, DevOps practices, and version control systems (e.g., Git, Azure DevOps).
</li><li>Experience implementing data governance and observability tools.
</li><li>Strategic mindset with the ability to balance technical depth and business impact.
</li></ul>Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required:
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation {+ 24 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements
Not Specified
Available for Work Visa Sponsorship?
No
Government Clearance Required?
No
Job Posting End Date</div>

ETIC, Data Engineer, Manager

<div>Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics &amp; AI
Management Level
Manager
Job Description &amp; Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
 
 
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Responsibilities:
1.Design and build robust streaming and batch data pipelines with AWS Glue, Lambda, Kinesis Data Streams/Firehose, Amazon MSK (Kafka), and Step Functions. 2.Architect end-to-end systems for real-time ingestion, processing, and analytics, leveraging Kinesis, MSK, Managed Flink, EMR, and Lambda for low-latency, high-availability operations. 3.Implement batch ETL pipelines using Glue, EMR (Spark/Hadoop), and S3, optimizing for cost and performance while handling large-scale datasets. 4.Integrate source systems (IoT, logs, transactional DBs, third-party feeds) and downstream destinations (Redshift, S3, DynamoDB, OpenSearch, Aurora, etc.). 5.Design and implement architectures supporting event-driven microservices, streaming analytics, materialized views, and near-real-time dashboards. 6.Ensure scalability, durability, ordering, and fault-tolerance in stream storage, using Kinesis/MSK and S3 for replay, backfill, and recovery scenarios. 7.Standardize patterns for Change Data Capture (CDC), late/duplicate data handling, data enrichment, stream normalization, and schema evolution. 8.Govern data security (encryption, access control, network isolation), ensure compliance, and embed monitoring/observability pipelines for SLA/SLO adherence. Required Experience and Skills 1.Experience in data engineering/architecture, including significant leadership in AWS cloud data platforms. 2.Expert in designing streaming architectures with Kinesis, Kafka (MSK), Managed Flink, Lambda, and Step Functions. 3.Strong proficiency in batch ETL (AWS Glue, EMR, Spark/Hadoop), large-scale data lake/lakehouse implementation (S3, Delta Lake, Redshift). 4.Hands-on experience architecting hybrid streaming/batch workflows for analytics, reporting, ML, and near-real-time applications. 5.Deep understanding of distributed computing, parallelization, and fault-tolerance strategies for high-velocity, high-volume data. 6.Familiarity with real-time dashboards, API publication (REST, WebSockets), and materialized views for user-facing analytics. Proficient in network/security controls, IAM design, encryption (KMS), and data governance. Experience with DevOps/IaC (CloudFormation, Terraform). 7.Excellent communication and stakeholder leadership; ability to translate business requirements to technical solution patterns.
Mandatory skill sets: AWS Data Architect
Preferred skill sets:
AWS Data Architect
Years of experience required:
8-12 Years
Education qualification: B. Tech/MBA/MCA / M. Tech
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Technology, MBA (Master of Business Administration), Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Data Engineering
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date</div>

IN_Manager_ AWS Data Architect_D&A_Advisory_PAN India

Client of Tandem Search

Job Title: Technical Manager Data &amp; Artificial Intelligence (AI) 
Location: Dubai, UAE/Riyadh, KSA 
Firm: Big4 
 Role Overview 
We are seeking a Data &amp; AI Technical Manager to play a key role in designing, implementing, and managing advanced data and AI solutions for our clients. This role combines deep technical expertise with strong consulting skills to deliver innovative, scalable, and business-driven outcomes. As a Technical Manager, you will work with cross-functional teams, manage solution delivery, and collaborate closely with senior stakeholders to ensure the successful execution of Data &amp; AI transformation programs.
 Key Responsibilities 
<ul>
 <li>
 Solution Design &amp; Delivery 
<ul>
 <li>
 Lead the design, architecture, and implementation of data and AI platforms, pipelines, and solutions.
 </li>
 <li>
 Develop scalable models and systems in machine learning, AI, advanced analytics, and data engineering.
 </li>
 <li>
 Ensure solutions align with client objectives, compliance requirements, and industry best practices.
 </li>
 <li>
 Drive end-to-end project delivery, from requirements gathering to deployment and handover.
 </li>
 </ul>
 </li>
 <li>
 Technical Leadership 
<ul>
 <li>
 Provide subject matter expertise in cloud ecosystems (Azure, AWS, GCP), data engineering frameworks, and AI/ML tools.
 </li>
 <li>
 Guide technical teams on model development, MLOps, data governance, and responsible AI practices.
 </li>
 <li>
 Stay current with emerging AI and data technologies to embed innovation in client solutions.
 </li>
 </ul>
 </li>
 <li>
 Client Engagement 
<ul>
 <li>
 Translate business requirements into technical solutions, ensuring business value is realized.
 </li>
 <li>
 Work closely with senior stakeholders and C-level executives to explain complex technical concepts in simple, actionable terms.
 </li>
 <li>
 Support pre-sales and business development efforts by preparing proposals, demos, and solution presentations.
 </li>
 </ul>
 </li>
 <li>
 Team &amp; Practice Development 
<ul>
 <li>
 Manage and mentor data scientists, engineers, and analysts in delivering high-quality client engagements.
 </li>
 <li>
 Contribute to capability building, internal knowledge sharing, and the growth of the Data &amp; AI practice.
 </li>
 <li>
 Collaborate with global technology partners (Microsoft, AWS, Google, OpenAI) to bring cutting-edge solutions to market.
 </li>
 </ul>
 </li>
</ul>
 Qualifications &amp; Experience 
<ul>
 <li>
 Education: Bachelor s degree in Computer Science, Engineering, Data Science, or related field; Master s preferred.
 </li>
 <li>
 Experience: 8 12 years in data engineering, advanced analytics, or AI/ML, with at least 3 5 years in a managerial/technical leadership role.
 </li>
 <li>
 Proven track record in delivering end-to-end data and AI projects within large organizations or consulting firms.
 </li>
 <li>
 Strong knowledge of data platforms (Azure Synapse, Snowflake, BigQuery, Databricks), machine learning frameworks (TensorFlow, PyTorch, Scikit-learn), and data governance tools.
 </li>
 <li>
 Hands-on experience with ETL pipelines, APIs, MLOps, and cloud-native architectures.
 </li>
 <li>
 Excellent communication and stakeholder management skills, with experience presenting to senior executives.
 </li>
</ul>
 Skills &amp; Competencies 
<ul>
 <li>
 Strong technical expertise in data architecture, ML model development, and cloud-native solutions.
 </li>
 <li>
 Ability to manage complex, multi-disciplinary projects under tight timelines.
 </li>
 <li>
 Demonstrated leadership in team management and mentoring.
 </li>
 <li>
 Passion for innovation, problem-solving, and applying AI to real-world business challenges.
 </li>
</ul>

Data & AI Technical Manager

Envision Employment Solutions

Envision Employment Solutions is currently looking for a Delivery Manager for one of our partners, a global leader in the IT Services and IT Consulting.
 
Responsibilities: 
<ul>
<li>Delegate technical responsibilities and monitor the progress of team development</li>
<li>Responsible for staffing requirements, team performance and development, and departmental results</li>
<li>Serve as the team's representative to the rest of the company</li>
<li>Make sure the team is fully trained and able to perform their jobs</li>
<li>Contributing to making key decisions for technical issues related to the company</li>
<li>Conducting employee reviews, handling employee complaints, and dividing the workload among members of the team</li>
<li>Define and manage team KPI's and SLAs to ensure business objectives are being met</li>
<li>Develop and implement strategic objectives to ensure achievement of profitability goals and high level of customer satisfaction.</li>
<li>Develop centric KPIs/SLAs</li>
</ul>
Requirements: 
<ul>
<li>Bachelor’s degree in computer science, Data Engineering, Information Systems, or related discipline.</li>
<li>Master’s degree preferred.</li>
<li>10-12 years of work experience.</li>
<li>Delivery of projects end-to-end</li>
<li>Customer interfacing</li>
<li>Proposals and Presentations writings</li>
<li>Technical Knowledge of the data management field with its latest updates</li>
<li>Excellent people management skills</li>
<li>Exceptional communication and reporting skills</li>
<li>Able to give clear instructions and set expectations</li>
<li>Able to assess and set team's long-term goals</li>
<li>Outstanding leadership skills and ability to delegate responsibilities effectively</li>
<li>Ability to mentor others, clearly explain complex requirements and help developers understand them</li>
<li>Have Decision-making and organizational abilities to help you effectively manage workload</li>
<li>Able to assess technological challenge and then keep his team updated and well trained on developing realistic and effective solutions</li>
<li>Experience in Analysis, Design, Development, Implementation, Testing and Support of Data Warehousing and Data Integration Solutions and ETL data pipelines</li>
<li>Experience ETL, SQL, UNIX/Linux, Big Data distributed systems, various programming languages like Java and Python, orchestration tools and processes or other directly related experience.</li>
<li>Good experience in end-to-end implementation of DW & BI projects, especially in data warehouse and mart developments</li>
<li>Experience in Relational Modeling, Dimensional Modeling, Modeling of Unstructured Data and business process relationships</li>
<li>Experience with Big data technologies</li>
<li>Good understanding of Data integration, Data quality paradigms and data governance/ data architecture concepts</li>
<li>Experience working in Agile framework and project management methodologies</li>
<li>Full lifecycle project experience as a developer in designing and developing ETL jobs.</li>
</ul>

Delivery Manager

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