etl engineer

YO IT CONSULTING

<div><div>Job Type: Contractor
Location: Remote
<h3 class="jobSectionHeader">Role Description</h3>
If you&rsquo;re a senior Data Engineer who thrives on precision, systems thinking, and building reliable data foundations, this is a unique opportunity to contribute directly to how the next generation of AI systems reason about data infrastructure, pipelines, and analytics workflows. We&rsquo;re looking for experienced Data Engineers who understand modern data stacks, ETL/ELT architecture, orchestration, data modeling, warehouse design, quality validation, governance, and production-scale reliability.Your work will help strengthen how AI models reason through complex data engineering scenarios, identify technical errors, and communicate implementation guidance clearly.</div>
<div><h3 class="jobSectionHeader">Your Profile</h3>
<ul><li>4+ years of professional experience in data engineering, with significant hands-on work designing, building, and maintaining production-grade data pipelines.</li>
<li>Deep knowledge of SQL, data modeling, ETL/ELT architecture, orchestration frameworks, warehouse/lakehouse patterns, and modern data stack tools such as dbt, Airflow, Snowflake, BigQuery, Databricks, Fivetran, or similar platforms.</li>
<li>Strong understanding of distributed data systems, batch and streaming workflows, schema design, data validation, data observability, lineage, and pipeline reliability.</li>
<li>Proven experience optimizing complex SQL queries, troubleshooting data quality issues, designing scalable transformations, and supporting analytics or machine learning-ready datasets.</li>
<li>Demonstrated experience in translating ambiguous business or technical requirements into reliable data models, pipeline designs, and implementation plans.</li>
<li>Bachelor&rsquo;s degree in Computer Science, Data Engineering, Information Systems, Statistics, Engineering, or a related technical field; equivalent professional experience will also be considered.</li>
<li>Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.</li>
</ul></div><div><h3 class="jobSectionHeader">Key Responsibilities</h3>
<ul><li>Evaluate AI-generated answers to data engineering prompts for technical accuracy, completeness, clarity, and real-world feasibility.</li>
<li>Challenge advanced language models with complex Data Engineer scenarios involving SQL, Python, ETL/ELT design, orchestration, warehousing, data modeling, and pipeline reliability.</li>
<li>Review and refine AI-generated prompts, responses, rubrics, and reference answers to ensure they reflect senior-level data engineering judgment.</li>
<li>Provide structured feedback that identifies incorrect assumptions, missing constraints, weak reasoning, inefficient implementations, or unsafe recommendations.</li>
<li>Shape AI communication standards by helping models explain data architecture, debugging steps, tradeoffs, and implementation patterns clearly and responsibly.</li>
<li>Support benchmarking efforts by evaluating model performance across realistic data engineering workflows, edge cases, and failure modes.</li>
<li>Develop and review high-quality examples that demonstrate strong reasoning around pipeline design, data quality checks, data contracts, schema evolution, and system scalability.</li></ul></div></div>

Data Engineer – Remote

BFG Enterprise Services

<div>Description:

Location: Remote (U.S. Only) 
Environment: Government-Furnished Equipment (GFE), HIPAA-Compliant 
Client: Department of Veterans Affairs (VA) &ndash; SPGP Program 
Type: Full-Time / Contract
Position Overview
BFG Enterprises is seeking an AWS Data Platform Engineer (Integration &amp; Operations) to support and stabilize a cloud-based data platform for the Staff Sergeant Parker Gordon Fox Suicide Prevention Grant Program (SPGP).
This role focuses on system reliability, data pipeline validation, environment management, and integration stability across AWS services and external systems. The engineer will work across development, operations, and data workflows to ensure the platform functions consistently and securely in a federal, HIPAA-compliant environment.
Requirements:

Key Responsibilities<ul><li>
Operate, monitor, and troubleshoot ETL pipelines running on AWS Lambda (Node.js)</li><li>
Validate data flows from external systems through ETL into Amazon DocumentDB</li><li>
Diagnose and resolve issues involving APIs, authentication (JWT), and data inconsistencies</li><li>
Manage deployments across DEV, PPD, and PROD environments</li><li>
Execute and verify safe code deployments from GitHub</li><li>
Monitor logs and system behavior using AWS CloudWatch</li><li>
Manage and update SSL/TLS certificates (DigiCert, Venafi)</li><li>
Ensure secure connectivity to databases and services</li><li>
Perform database queries and validation in DocumentDB (MongoDB-compatible)</li><li>
Support and improve CI/CD pipelines using GitHub Actions or similar tools</li><li>
Maintain documentation and standard operating procedures</li><li>
Participate in required meetings with VA, MITRE, and internal stakeholders</li></ul>
Required Qualifications<ul><li>
3+ years of experience in cloud engineering, data engineering, or platform engineering</li><li>
Strong experience with Node.js and JavaScript</li><li>
Hands-on experience with AWS Lambda</li><li>
Experience troubleshooting ETL or data processing workflows</li><li>
Experience working with REST APIs, including authentication (JWT, API keys, OAuth)</li><li>
Experience with MongoDB or Amazon DocumentDB</li><li>
Familiarity with GitHub (branching, commits, pull requests)</li><li>
Experience using logs for debugging (e.g., CloudWatch)</li><li>
Ability to work across multiple environments (DEV, staging, PROD)</li><li>
Strong problem-solving and troubleshooting skills</li><li>
Clear communication and documentation ability</li></ul>
Preferred Qualifications<ul><li>
Experience with GitHub Actions or CI/CD pipelines</li><li>
Experience with AWS EventBridge (scheduled jobs)</li><li>
Experience managing SSL/TLS certificates</li><li>
Familiarity with Docker or container-based systems</li><li>
Experience in federal, healthcare, or HIPAA-compliant environments</li><li>
Exposure to AWS GovCloud</li></ul>
Security and Compliance Requirements<ul><li>
Must be comfortable working on a GFE (Government-Furnished Equipment) laptop</li><li>
Must adhere to HIPAA and federal data security requirements</li><li>
Must follow strict access control, credential handling, and system usage policies</li></ul>
What Success Looks Like<ul><li>
ETL pipelines run reliably across all environments</li><li>
External API integrations are stable and monitored</li><li>
Deployments are controlled and do not introduce risk</li><li>
Data in DocumentDB is accurate and validated</li><li>
Issues are quickly identified and resolved</li><li>
Operational processes are documented and repeatable</li></ul>
How to Apply
Please submit a resume and a brief description of relevant experience with AWS, ETL, APIs, and Node.js.</div>

AWS Platform Engineer (Integration & Operations)

Comspark Innov & Infra

We&rsquo;re Hiring: ETL / Integration Developer (Banking Domain)Exciting opportunity for experienced ETL / Integration Developers to work on high-impact banking projects in the Middle East!Location: Riyadh, Saudi Arabia (Onsite) Experience: 5+ Years Industry: Banking Joining: ImmediateKey Skills Required:<ul><li>Strong ETL &amp; Data Integration experience</li><li>Hands-on with Informatica / SSIS / Talend</li><li>Strong SQL &amp; Database knowledge</li><li>Experience in Banking / Financial domain</li><li>Arabic &amp; English communication (Mandatory)</li></ul>Candidates with experience in API integrations, Data Governance, and Cloud platforms will have an added advantage.Work Location: In person

ETL / Integration Developer

MERCOR

<div><h2 class="jobSectionHeader">About Mercor</h2>
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You&rsquo;ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
We&rsquo;re looking for someone who wants to bring a full-stack perspective to data. As a Software Engineer supporting our Data function, you will be responsible for creating and maintaining pipelines that enable our Data Science, Engineering, and Product teams, and the wider Mercor organization.
Your focus will be on data reliability, availability, and timeliness, with a focus on collaboration (and significant operational crossover with) our Data Science team and the many partner functions.
What You&rsquo;ll Work On<ul><li>
Building robust pipelines to ingest, transform, and consolidate data from diverse sources (e.g., MongoDB, Airtable, PostHog, production databases).</li><li>
Designing dbt models and transformations to standardize and unify many disparate tables into clean, production-ready schemas.</li><li>
Implementing scalable, fault-tolerant data workflows with Fivetran, dbt, SQL, and Python.</li><li>
Partnering with engineers, data scientists, and business stakeholders to ensure data availability, accuracy, and usability.</li><li>
Owning data quality and reliability across the stack, from ingestion through to consumption.</li><li>
Continuously improving pipeline performance, monitoring, and scalability.</li></ul> 
What We&rsquo;re Looking For<ul><li>
Proven experience in data engineering, with strong knowledge of SQL, Python, and modern data stack tools (Fivetran, dbt, Snowflake or similar).</li><li>
Experience building and maintaining large-scale ETL/ELT pipelines across heterogeneous sources (databases, analytics platforms, SaaS tools).</li><li>
Strong understanding of data modeling, schema design, and transformation best practices.</li><li>
Familiarity with data governance, monitoring, and quality assurance.</li><li>
Comfort working cross-functionally with engineering, product, and operations teams.</li><li>
Bonus: prior experience supporting machine learning workflows or analytics platforms.</li></ul>
Why Mercor<ul><li>
Impact: Your work powers how the world&rsquo;s leading AI labs train and test their models.</li><li>
Learning: Get early insights into frontier model capabilities months before the market.</li><li>
Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.</li></ul>
Benefits<ul><li>
Generous equity grant vested over 4 years</li><li>
A $10K housing bonus (if you live within 0.5 miles of our office)</li><li>
A $1K monthly stipend for meals</li><li>
Free Equinox membership</li><li>
Health insurance</li></ul>
Compensation Range: $130K - $500K</div>

Data Engineer

Smart Working Solutions

<div>About Smart Working 
At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn&rsquo;t just another remote opportunity - it&rsquo;s about finding where you truly belong, no matter where you are. From day one, you&rsquo;re welcomed into a genuine community that values your growth and well-being.

Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you&rsquo;re empowered to grow personally and professionally.

Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.

About the Role 
We're looking for a Senior Data Engineer to become a cornerstone of our data platform team. This is a long-term, strategic role, not a short sprint. You'll be embedded in a collaborative engineering and analytics team, working across the full data lifecycle: ingestion, transformation, modelling, and surfacing insights through Looker. You'll work closely with stakeholders across commercial, product, and marketing to ensure data is reliable, scalable, and meaningful. 
 
You'll be given real ownership. This is a role for someone who wants to shape standards, improve the architecture, and grow with a brand that takes its data seriously.
<h3 class="jobSectionHeader">
Responsibilities</h3><ul>
<li>Design, build, and maintain robust ETL/ELT pipelines that move data from source systems into Google BigQuery, ensuring reliability, scalability, and observability at every stage.</li>
<li>Develop and enforce data models and schema standards using best-practice SQL and dimensional modelling principles, with a focus on clarity, reuse, and performance.</li>
<li>Own the Google BigQuery environment, optimising queries, managing costs, enforcing data governance, and ensuring the platform scales alongside the business.</li>
<li>Build and maintain Looker explores, LookML models, and dashboards that translate complex datasets into clear, actionable business intelligence for non-technical stakeholders.</li>
<li>Work across the full Google Cloud Platform stack, including Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, and Composer, to architect end-to-end data solutions.</li>
<li>Partner with analytics, engineering, and commercial teams to understand data requirements and translate business problems into scalable technical solutions.</li>
<li>Champion data quality and testing frameworks, implementing monitoring and alerting so that issues are caught early and resolved quickly.</li>
<li>Contribute to documentation, coding standards, and architectural decision records so the team can move fast with confidence.</li>
<li>Mentor junior data team members and set the bar for engineering rigour across the data function.</li>
<li>Stay current with developments in the modern data stack and proactively recommend tooling or process improvements where appropriate.</li>
</ul><h3 class="jobSectionHeader">Requirements</h3><ul>
<li>5+ years of experience in SQL and data modelling, with strong command of dimensional modelling, star schemas, and performance optimisation.</li>
<li>3+ years working with Google BigQuery in a production environment.</li>
<li>3+ years hands-on experience with Google Cloud Platform (Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, Composer).</li>
<li>3+ years building and maintaining ETL/ELT pipelines at scale.</li>
<li>1+ year working with Looker and LookML to deliver business-facing dashboards and data products.</li>
<li>Demonstrable experience leading at least one data project end-to-end, from scoping through to delivery.</li>
<li>Able to communicate clearly with non-technical stakeholders about data limitations, timelines, and trade-offs.</li>
<li>Comfortable making pragmatic architecture decisions in a cloud-native, modern data stack environment.</li>
</ul><h3 class="jobSectionHeader">Nice to Have</h3><ul>
<li>Experience with dbt (Data Build Tool) for transformation layer management and testing.</li>
<li>Familiarity with orchestration tools such as Apache Airflow or Cloud Composer.</li>
<li>Python skills for pipeline scripting, data validation, or automation.</li>
<li>Background in retail, ecommerce, or fashion, understanding how data flows across commercial and digital channels.</li>
<li>Exposure to real-time or streaming data pipelines using Pub/Sub or Dataflow.</li>
<li>Experience with Terraform or Infrastructure-as-Code practices in a GCP context.</li>
<li>Familiarity with data governance frameworks, cataloguing, and lineage tracking.</li>
</ul><div>
At Smart Working, you&rsquo;ll never be just another remote hire.

Be a Smart Worker - valued, empowered, and part of a culture that celebrates integrity, excellence, and ambition.

If that sounds like your kind of place, we&rsquo;d love to hear your story.
</div>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div>

Senior Data Engineer (GCP, BigQuery, Looker), PK [AS233]

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Senior Data Engineer (GCP, BigQuery, Looker), PK [AS233]