Senior Data Engineer

Why Blue Coding? 

At Blue Coding, we specialize in hiring excellent developers and amazing people from all over Latin America and other parts of the world. For the past 11 years, we've helped cutting-edge companies in the United States and Canada build great development teams and develop great products. Large multinationals, digital agencies, Saas providers, and software consulting firms are just a few of our clients. Our team of over 150 engineers, project managers, QA, UX/UI designers, and many more is distributed in more than 10 countries across the Americas. We are a fully remote company working with a wide array of technologies, and we have expertise in every stage of the software development process.

Our team is highly connected, united, and culturally diverse, and our collaborators are involved in many initiatives around the world, from wildlife preservation to volunteering at local charities. We stand for honesty, fairness, respect, efficiency, hard work, and cooperation.

This position is open exclusively to candidates based in LATAM countries.

What are we looking for?

We're hiring a Senior Data Engineer to design and build a next-gen data platform for one of our clients. Speaking both Spanish and English at a fluent level is a must.

You'll lead the end-to-end ingestion, transformation, and governance of document-centric datasets stored in S3 (or an alternative object store) for millions of documents, and stand up a scalable data lake and warehouse that powers analytics, dashboards, and AI model training. Powering AI models is the end goal; your involvement in this process is the first step, and we expect clear documentation.

This is a hands-on technical role with ownership of architecture and standards, as well as the opportunity to mentor a small team in the future.

You will engage directly with the client's team to gather requirements, clarify technical trade-offs, and provide regular status updates, while reporting internally on project milestones, risks, and dependencies. 

This role balances hands-on engineering with clear stakeholder communication, turning client feedback into actionable sprint plans and keeping both the client and our internal leadership aligned on progress, quality, and timelines.

• Design and build an AWS-first data platform: stand up an S3-based (or equivalent) data lake, Glue Data Catalog/Lake Formation, and a performant warehouse layer (Redshift/Snowflake/Athena) using medallion (bronze/silver/gold) patterns.
• Implement a robust ETL/ELT solution for document data, including OCR (Textract), text parsing, metadata enrichment, schema inference, incremental loads, partitioning, and optimization for large-scale semi-structured/unstructured files.
• Make data AI-ready: create curated, versioned training datasets, embeddings/feature pipelines, as well as ML-friendly exports for SageMaker/Bedrock or downstream services; prepare for a future AI developer to plug in models easily.
• Orchestrate and productionize pipelines with Airflow/MWAA or Step Functions/Lambda; containerize where necessary (ECS/EKS) and deploy with Terraform or AWS CDK, along with CI/CD (CodePipeline/GitHub Actions). Still not defined, you are expected to suggest the best solutions that cater to the client's requirements and budgets.
• Establish data quality, lineage, and governance: Utilize Great Expectations/Deequ checks, OpenLineage/Marquez, fine-grained permissions with Lake Formation, and perform cost/performance monitoring. Still not defined, you are expected to suggest the best solutions that cater to the client's requirements and budgets.
• Partner with Analytics/BI to provision trusted marts powering dashboards (QuickSight/Power BI/Tableau) and self-serve queries. Still not defined, you are expected to suggest the best solutions that cater to the client's requirements and budgets.
• Meet directly with the client's team to gather requirements, communicate trade-offs, and demo progress; report internally on milestones, risks, and dependencies
• Manage your own delivery process, including backlog grooming, sprint planning, estimates, stand-ups, reviews, and retrospectives. As well as owning outcomes end-to-end as the initial solo engineer

• 6–10+ years in data engineering with 3+ years building production workloads on AWS; expert-level Python and SQL plus strong Spark (Glue/EMR/Databricks).
• Proven experience designing and operating data lakes/warehouses at scale, including file formats (Parquet/Delta/Iceberg/Hudi), partitioning, and performance/cost tuning.
• Hands-on document ETL: OCR pipelines, text/metadata extraction, schema design, and incremental processing for millions of files.
• Solid orchestration and DevOps chops: Airflow/MWAA or Step Functions, Docker, Terraform/CDK, and CI/CD best practices.
• Data governance mindset: lineage, quality frameworks, IAM least privilege, KMS, VPC endpoints/private networking, secrets management, and compliance awareness (e.g., SOC 2/ISO
• Practical ML enablement: crafting reproducible, versioned datasets; experience with embeddings/feature pipelines and at least one vector-store pattern (OpenSearch/pgvector/etc).
• Excellent stakeholder communication and leadership: comfortable being the first and only data engineer, translating client needs into clear sprint goals, and later mentoring/partnering with an AI developer as the team grows.

• Salary in USD
• 100% Remote

Ready to learn more? Apply below