senior database engineer

<div>
 Keep the databases behind a national platform fast, available, and safe, operating enterprise PostgreSQL and a polyglot estate of vector, graph, and search stores that power its applications and its AI, on sovereign infrastructure with no managed cloud to fall back on.
 <br/>
 RQMNA runs the sovereign data platforms that millions of citizens depend on every time they reach their government.
 <br/>
 <br/>
 We are hiring a Senior Database Engineer, on site in Muscat, to own the databases a national platform runs on, from transactional core to AI vector stores.
 <br/>
 <br/>
 What you'll do: Operate the platform's polyglot databases at national scale, fast, resilient, recoverable, and infused with AI/ML/DL/RL
 <br/>
 <br/>
 Key Responsibilities:
 <br/>
 Operate enterprise PostgreSQL as the primary transactional database across the platform, and tune it for performance under national load
 <br/>
 Design and run high availability, replication, and failover, with backup, recovery, and tested point in time restore
 <br/>
 Operate the vector databases behind the platform's AI: Milvus for large scale retrieval and RAG, and pgvector for vectors co-located in PostgreSQL
 <br/>
 Operate the graph database (Neo4j) for case correlation and entity relationships, and the search engine (Elasticsearch) for hybrid and full text search
 <br/>
 Run the specialized PostgreSQL workloads in production: geospatial (PostGIS), time series (TimescaleDB), and document (JSONB)
 <br/>
 Operate the in-memory distributed cache, a secondary enterprise relational store for select product catalogs, and the search-side vector retrieval
 <br/>
 Manage S3 compatible object storage and immutable, long retention archival, and plan capacity across the whole estate
 <br/>
 Run upgrades and patching with no surprise downtime, harden every store with encryption and access control, and automate database operations as code
 <br/>
 <br/>
 What makes you a fit:
 <br/>
 You have operated production databases at scale, and carried the pager for them
 <br/>
 You are a deep PostgreSQL engineer: replication, high availability, backup and recovery, and performance tuning
 <br/>
 You have run at least one vector database in production, such as Milvus or pgvector, for AI or RAG workloads
 <br/>
 You have operated a graph database such as Neo4j, or a search engine such as Elasticsearch, or you can clearly pick them up
 <br/>
 You are comfortable across a polyglot estate, relational, vector, graph, search, time series, and cache, and you pick the right store per workload
 <br/>
 You are at home on premises and sovereign, where there is no managed cloud database to lean on
 <br/>
 You hold a Bachelor's or higher in Computer Science, Engineering, or a related field, or equivalent depth
 <br/>
 You automate operations, take security and recoverability seriously, and you test your backups
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 Bonus points for very large datasets, AI data infrastructure, or government and regulated environments
 <br/>
 Fluent English required; Arabic is a valuable advantage
 <br/>
 <br/>
 If you keep the data layer fast and unbreakable, from transactions to AI vectors, a nation will run on it. Apply.
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 <br/>
 #Database #PostgreSQL #VectorDatabase #DBA #Hiring
</div>


Senior Database Engineer

Trickle Up

<div><p>We are looking for a Senior Data Engineer to design, build, and maintain enterprise-scale data platforms on Azure. You will own end-to-end data pipelines from raw ingestion to curated, analytics-ready gold layers while driving data quality standards, mentoring junior engineers, and collaborating directly with product and AI teams.</p><b><br>
Requirements</b><p><b><br>
Pipeline Design &amp; Architecture</b></p><ul><li>Architect and manage scalable ETL/ELT pipelines using Medallion Architecture (Bronze  Silver  Gold)</li><li>Design ADF pipelines, data models, and schemas optimised for performance and maintainability</li><li>Build near real-time and batch ingestion solutions across structured and semi-structured sources</li></ul><p><b>
Data Governance &amp; Quality</b></p><ul><li>Implement data quality checks, validation frameworks, and lineage tracking across pipeline layers</li><li>Enforce security controls, access policies, and compliance requirements on ADLS Gen 2 and Azure SQL</li><li>Monitor pipeline SLAs, diagnose performance bottlenecks, and own incident resolution</li></ul><p><b>
Engineering Excellence</b></p><ul><li>Drive CI/CD adoption for data pipelines using Azure DevOps or equivalent tooling</li><li>Define and enforce coding standards, peer-review practices, and documentation norms</li><li>Contribute to Al agent development initiatives as a data platform subject-matter expert</li></ul><p><b>
Collaboration &amp; Mentorship</b></p><ul><li>Partner with data scientists, analysts, and product managers to translate requirements into reliable data products</li><li>Mentor junior engineers through code reviews, design discussions, and structured knowledge sharing</li><li>Participate in Agile ceremonies and contribute to sprint planning, backlog refinement, and technical estimation</li></ul><p></p><p><b>
EXPERIENCE &amp; REQUIREMENTS</b></p><p></p><p><b>
Must-Have</b></p><ul><li>5-6 years of hands-on Data Engineering experience in production environments</li><li>Deep expertise in Azure ecosystem &mdash; ADLS Gen 2, ADF, Azure SQL Database, and Delta Lake</li><li>Strong command of PySpark, Python, and SQL for large-scale data transformation</li><li>Proven track record building and operating Medallion Architecture (Bronze/Silver/Gold) on Azure</li><li>Experience designing data warehouses and data lake solutions at enterprise scale</li><li>Familiarity with CI/CD pipelines, version control (Git), and DevOps practices in a data context</li></ul><p>
Nice-to-Have</p><ul><li>Exposure to AWS or GCP in addition to Azure</li><li>Experience supporting or building Al/ML data pipelines and feature stores</li><li>Knowledge of streaming frameworks &mdash; Kafka, Event Hubs, or Spark Structured Streaming</li><li>Azure certifications (DP-203, AZ-900 or equivalent)</li></ul></div><p></p>

Senior Data Engineer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.<br>
</li>
<li>5 years of experience in software development for core system-level software such as databases, operating systems, or kernels.</li>
<li>5 years of programming experience in C, C++ or Java.</li>
<li>3 years of experience building and developing large-scale infrastructure or distributed systems.</li>
<li>3 years of experience with distributed computing.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree or PhD in Computer Science or related technical fields.<br>
</li>
<li>Experience with database internals (e.g., PostgreSQL, GraphQL, OLTP databases), transactional systems, compilers, or data storage.</li>
<li>Experience with AI Algorithms.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
As a Software Engineer focusing on semantic search for AlloyDB, you'll have the opportunity to contribute to AI/GenAI features within an innovative, Google open-source PostgreSQL-based database product. You'll play a key role in building new database features that integrate advanced semantic search capabilities.</p><div></div><div><br>
You'll be instrumental in designing, developing, and implementing semantic search capabilities within AlloyDB, focusing on delivering robust, scalable, and high-performance features.</div><div></div><div><br>
You'll be involved in bringing novel innovations to the core database engine, including areas like query processing, indexing, and vector embedding. Your work will directly impact our enterprise customers, empowering them to leverage the power of semantic search within their AlloyDB applications.</div><p>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</p>
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
<br>
<br>
US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits<br>
<br>
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Design, develop, and implement semantic search capabilities within AlloyDB, focusing on delivering robust, scalable, and high-performance features.</li>
<li>Collaborate with engineers across various teams to understand requirements and build effective semantic search solutions.</li>
<li>Take ownership of specific components and contribute to the team's technical discussions, continuously learning and applying best practices.</li>
<li>Build new database features that integrate advanced semantic search capabilities.</li>
<li>Contribute to key technical projects and work within a fast-moving, innovative environment.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Software Engineer, AlloyDB Semantic Search

GSSTech Group

<div><p>We are looking for a highly skilled Senior Data Engineer with strong expertise in PySpark, Python, and Big Data technologies to design, build, and optimize scalable data platforms and pipelines. The ideal candidate will work closely with Data Scientists, Business Analysts, and Analytics Delivery teams to develop high-performance analytics solutions and support advanced data science initiatives.</p><b><br>
Requirements</b><br>
<br>
Key Responsibilities<ul><li>
Collaborate with Analytics Delivery Leads and Lead Data Engineers to understand business requirements and deliver impactful data solutions.</li><li>
Work closely with Data Scientists and cross-functional teams to solve complex business problems through data engineering solutions.</li><li>
Manage data onboarding, data access, and stakeholder coordination for analytics initiatives.</li><li>
Design, develop, and maintain scalable, secure, and high-performance data pipelines.</li><li>
Acquire, ingest, process, and transform large-scale structured and unstructured datasets.</li><li>
Implement data engineering best practices for building reliable and production-ready data platforms.</li><li>
Perform data wrangling, cleansing, transformation, and feature engineering for machine learning and analytics use cases.</li><li>
Design and develop modular data pipelines to generate reusable features and modeling datasets.</li><li>
Build and optimize data architectures supporting advanced analytics and machine learning workloads.</li><li>
Contribute to data platform design by selecting appropriate technologies across Big Data, SQL, and NoSQL ecosystems.</li><li>
Ensure data quality, integrity, governance, security, and scalability across the data lifecycle.</li><li>
Participate in Agile squads and collaborate effectively with stakeholders across business and technology teams.</li><li>
Contribute to enterprise data architecture strategy and roadmap aligned with business objectives.</li></ul>
Required Technical SkillsCore Data Engineering<ul><li>
Strong experience in Data Engineering and Big Data solutions.</li><li>
Expert-level proficiency in PySpark.</li><li>
Strong programming experience in Python.</li><li>
Experience building large-scale distributed data processing pipelines.</li></ul>
Data Processing &amp; ETL<ul><li>
Data Ingestion</li><li>
Data Transformation</li><li>
Data Wrangling</li><li>
Data Preparation</li><li>
Data Modeling</li><li>
Feature Engineering</li><li>
ETL/ELT Development</li><li>
Batch Processing</li><li>
Data Pipeline Development</li></ul>
Big Data Technologies<ul><li>
Apache Spark / PySpark</li><li>
Distributed Data Processing Frameworks</li><li>
Big Data Ecosystems</li></ul>
Database Technologies<ul><li>
Strong SQL expertise</li><li>
Experience with Relational Databases</li><li>
Experience with NoSQL Databases</li><li>
Data Warehousing Concepts</li></ul>
Cloud &amp; Analytics Platforms (Preferred)<ul><li>
Azure Data Platform</li><li>
AWS Data Services</li><li>
Google Cloud Data Services</li><li>
Databricks</li><li>
Hadoop Ecosystem</li></ul>
Machine Learning Data Support<ul><li>
Feature Engineering for ML Models</li><li>
Data Preparation for Analytics and AI Use Cases</li><li>
Building Modeling and Feature Tables</li><li>
Supporting Data Science Workloads</li></ul>
Engineering Best Practices<ul><li>
Software Engineering Principles</li><li>
Data Pipeline Optimization</li><li>
Data Quality Management</li><li>
Performance Tuning</li><li>
Scalability &amp; Security</li><li>
Version Control (Git)</li><li>
CI/CD Concepts</li><li>
Documentation Standards</li></ul>
Required Soft Skills<ul><li>
Strong stakeholder management and communication skills.</li><li>
Experience working with Business Analysts, Data Scientists, and Product Teams.</li><li>
Ability to translate business requirements into scalable data solutions.</li><li>
Strong analytical and problem-solving skills.</li><li>
Experience working in Agile/Scrum environments.</li><li>
Ability to work independently and within cross-functional teams.</li></ul>
Preferred Qualifications<ul><li>
Experience working in enterprise-scale data platforms.</li><li>
Experience supporting machine learning and advanced analytics initiatives.</li><li>
Exposure to cloud-native data engineering solutions.</li><li>
Experience designing modern data architectures and data lake environments.</li></ul></div><p></p>

giftHEALTH

<div><h2 class="jobSectionHeader"><b>About Us</b></h2><p>
At Gifthealth, we're revolutionizing the way people experience healthcare by simplifying the process of managing prescriptions and health services. Our mission is to provide a seamless, personalized, and efficient healthcare experience for all our customers. We're a dynamic, innovative, and customer-centric company dedicated to making a positive impact on people's lives.</p><h3 class="jobSectionHeader"><b><br>
Position Summary</b></h3><p>
The Sr. Data Engineer is responsible for leading the design and architecture of Gifthealth's most critical data pipelines and platform components, establishing technical standards, and mentoring the broader engineering team. The ideal candidate has 6+ years of data engineering experience with demonstrated senior-level ownership, expert command of SQL, Python, and dbt, and the communication skills to align both technical and non-technical stakeholders on complex problems.</p><h3 class="jobSectionHeader"><b><br>
Key Responsibilities</b></h3><ul><li>
Lead the design and architecture of our most critical data pipelines and data platform components</li><li>
Set technical standards and best practices that elevate the entire data team</li><li>
Mentor and support junior and mid-level engineers through code reviews, pair programming, and knowledge sharing</li><li>
Own the health, scalability, and reliability of our orchestration infrastructure</li><li>
Partner with engineering, analytics, and leadership to shape the roadmap for our data platform</li><li>
Evaluate and introduce new tools and technologies to keep our stack modern and effective</li><li>
Ensure compliance and confidentiality of Personal Health Information across all data</li></ul><h3 class="jobSectionHeader"><b>
Qualifications</b></h3><ul><li><b>
Education</b>: Bachelor's Degree in mathematics, statistics, computer science, or other quantitative field and relevant work experience as a Senior Data Engineer</li><li><b>
Experience</b>: 6+ years of experience as a Data Engineer, with demonstrated senior-level ownership</li><li><b>
Skills</b>:
<ul><li>6+ years of experience as a Data Engineer, with demonstrated senior-level ownership</li>
<li>Expert proficiency in SQL and Python, with deep experience in Airflow or a comparable orchestrator</li>
<li>Strong track record with dbt, modern data warehouse platforms, and CI/CD pipelines</li>
<li>Experience mentoring engineers and contributing to team standards and culture</li>
<li>Ability to navigate ambiguity, make sound technical decisions, and drive projects to completion</li>
<li>Experience with AWS, Fivetran, and automated testing; Ruby experience is a plus</li>
<li>Excellent communication skills &mdash; you can align technical and non-technical stakeholders on complex problems</li>
<li>An excitement about what data can do for healthcare and patients</li>
</ul></li></ul><h3 class="jobSectionHeader"><b>Work Environment</b></h3><ul><li><b>
Location</b>: Remote</li></ul><h3 class="jobSectionHeader"><b>
Employment Classification</b></h3><p><b>
Status:</b> Full-time<br>
<b>FLSA:</b> Exempt</p><h3 class="jobSectionHeader"><b>
Equal Employment Opportunity (EEO) Statement</b></h3><p>
Gifthealth is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. All employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, transgender status, national origin, age, disability, veteran status, or any other legally protected status.</p><h2 class="jobSectionHeader"><b><br>
Disclaimer</b></h2><p>
This job description is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all responsibilities, duties, or skills required of personnel.Gifthealth reserves the right to modify job duties or descriptions at any time.</p></div>

<div>The Opportunity<br>
<br>
As a Data Engineer - Senior Associate, 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. As a Senior Associate, you will build meaningful client connections and learn how to manage and inspire others. You will navigate increasingly complex situations, grow your personal brand, and deepen your technical skills. You are expected to anticipate the needs of your teams and clients, and to deliver quality work. Embracing increased ambiguity, you will be comfortable when the path forward isn&rsquo;t clear, using these moments as opportunities to grow.<br>
<br>
In this role within our Technology Consulting practice, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. You will transform raw data into actionable insights, enabling informed decision-making and driving business growth. By using a broad range of tools, methodologies, and techniques, you will generate new ideas and solve problems, contributing to the overall strategy and objectives of your projects. This position offers a chance to develop a deeper understanding of the business context and how it is evolving.<br>
<br>
Responsibilities<br>
<br>
<ul><li>Designing and implementing data infrastructure and systems to facilitate efficient data processing and analysis</li><li>Developing and maintaining data pipelines, integration, and transformation solutions to support client needs</li><li>Utilizing Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities</li><li>Applying data architecture development and database management skills to optimize data solutions</li><li>Leveraging Apache Airflow and Apache Hadoop for scalable data processing and workflow management</li><li>Building and managing data lakes and warehouses to support large-scale data storage and retrieval</li><li>Confirming data quality and validation through rigorous testing and performance tuning</li><li>Collaborating with clients to understand their data requirements and deliver actionable insights</li><li>Utilizing Databricks Unified Data Analytics Platform for advanced data analytics and visualization</li><li>Implementing data security best practices to protect sensitive information and maintain compliance</li><li>Applying dimensional modeling and directed acyclic graphs (DAGs) for efficient data organization and processing</li><li>Supporting the development of data strategies to drive business growth and informed decision-making</li></ul><br>
What You Must Have<br>
<br>
<ul><li>At least a Bachelor's degree</li><li>At least 2 years of experience</li></ul><br>
What Sets You Apart<br>
<br>
<ul><li>Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics</li><li>Demonstrating proficiency in data engineering platforms like Databricks</li><li>Utilizing cloud platforms such as AWS and Microsoft Azure</li><li>Excelling in data architecture development and data modeling</li><li>Implementing data pipeline and data integration strategies</li><li>Navigating complex data environments with Apache Hadoop and Airflow</li><li>Applying critical thinking to solve data-related challenges</li></ul><p><br>
The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance</p><p></p><p>
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.</p><p></p><p>
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.</p><p></p><p>
Learn more about how we work: https://pwc.to/how-we-work</p><p></p><p>
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.</p><p></p><p>
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines<br>
<br>
#LI-Hybrid</p></div>

Data Engineer - Senior Associate

AlpacaJapan株式会社

<div><div><p><b>Who We Are:</b></p>
<p>
Alpaca is a US-headquartered self-clearing broker-dealer and brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more. Our recent Series D funding round brought our total investment to over $320 million, fueling our ambitious vision.</p>
<p>
Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 9 million brokerage accounts.</p>
<p>
Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of <b>opening financial services to everyone on the planet</b>. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it.</p>
<p>
Alpaca is proudly backed by top-tier global investors, including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Unbound, SBI Group, Derayah Financial, Elefund, and Y Combinator.</p><br>
<p></p>
<p><b>
Our Team Members:</b></p>
<p>
We're a dynamic team of 380+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond!<br>
<br>
We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values&mdash;Stay Curious, Have Empathy, and Be Accountable&mdash;and are ready to make a significant impact, we encourage you to apply.</p></div><div><p><b>
Your Role:</b> We are seeking a Senior Data Platform Engineer to design and develop the data management layer for our platform to ensure its scalability as we expand to larger customers and new jurisdictions. At Alpaca, data engineering encompasses financial transactions, customer data, API logs, system metrics, augmented data, and third-party systems that impact decision-making for both internal and external users. We process hundreds of millions of events daily, with this number growing as we onboard new customers.</p>
<p>
We prioritize open-source solutions in our data management approach, leveraging a Google Cloud Platform (GCP) foundation for our data infrastructure. This includes batch/stream ingestion, transformation, and consumption layers for BI, internal use, and external third-party sinks. Additionally, we oversee data experimentation, cataloging, and monitoring and alerting systems.</p>
<p>
Our team is 100% distributed and remote.</p>
<p><b>
Responsibilities:</b></p>
<ul>
<li>Design and oversee key forward- and reverse-ETL patterns to deliver data to relevant stakeholders.</li>
<li>Develop scalable patterns in the transformation layer to ensure repeatable integrations with BI tools across various business verticals.</li>
<li>Expand and maintain the Alpaca Data Lakehouse architecture's constantly evolving elements.</li>
<li>Collaborate closely with sales, marketing, product, and operations teams to address key data flow needs.</li>
<li>Operate the system and manage production issues in a timely manner.</li>
</ul>
<p><b>Must-Haves:</b></p>
<ul>
<li>7+ years of experience in data engineering, including 2+ years of building scalable, low-latency data platforms capable of handling &gt;100M events/day.</li>
<li>Proficiency in at least one programming language, with strong working knowledge of Python and SQL.</li>
<li>Experience with cloud-native technologies like Docker, Kubernetes, and Helm.</li>
<li>Strong hands-on experience with relational database systems and object storage implementations like Apache Iceberg.</li>
<li>Strong hands-on experience with Google Cloud Platform and its various data-related services (Composer, Dataproc, Datastream, etc.)</li>
<li>Experience in building scalable transformation layers, preferably through formalized SQL models (e.g., dbt).</li>
<li>Ability to work in a fast-paced environment and adapt solutions to changing business needs.</li>
<li>Experience with ETL orchestrators / frameworks like Apache Airflow and Airbyte.</li>
<li>Production experience with streaming systems like Kafka.</li>
<li>Exposure to infrastructure, DevOps, and Infrastructure as Code (IaaC), like Terraform.</li>
<li>Deep knowledge of distributed systems, storage, transactions, and query processing utilizing open-source distributed query engines like Trino (formerly PrestoSQL).</li>
<li>If you're passionate about data engineering and thrive in a dynamic startup environment, we'd love to hear from you!</li>
</ul></div><div><h3 class="jobSectionHeader"><b>How We Take Care of You:</b></h3>
<ul><li>Competitive Salary &amp; Stock Options</li>
<li>Health Benefits</li>
<li>New Hire Home-Office Setup: One-time USD $500</li>
<li>Monthly Stipend: USD $150 per month via a Brex Card</li>
</ul>
<p><i>Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.</i></p><br>
<p><i>
Recruitment Privacy Policy</i></p></div></div>

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