Data Engineer

Summary of the Role

We are looking for a Senior Data Engineer to design, build and operate production-grade data pipelines and warehousing solutions. You will turn messy, real-world data from internal and third-party sources into reliable, well-tested and automated data flows, working across Python, SQL, orchestration tools (Airflow/Dagster), cloud warehouses such as Snowflake and relational databases (PostgreSQL, SQL Server). This is a hands-on, execution-focused role for a self-directed engineer who can take projects from ambiguous requirements to production, partnering closely with business stakeholders, analysts and platform teams.

Desired Skills

• Full-Time availability
• Advanced English (C1) or above
• 5+ years of experience in data engineering, designing, building and automating production ETL/ELT pipelines
• Advanced, production-grade Python and SQL
• Deep experience with relational databases (PostgreSQL, SQL Server) and cloud data warehouses such as Snowflake, including data modeling and query performance tuning
• Hands-on experience with workflow orchestration tools such as Airflow or Dagster, and modern data stack tools such as dbt, Airbyte or Fivetran
• Experience with cloud infrastructure (AWS or Azure), Infrastructure as Code (Terraform), Docker and CI/CD pipelines (e.g., GitHub Actions, Azure DevOps)
• Proven track record building data validation, data quality checks and automated testing around pipelines

Responsibilities

• Design, build and maintain production data pipelines that integrate multiple internal and third-party data sources
• Refactor ad-hoc notebooks, spreadsheets and scripts into modular, well-tested and maintainable pipelines
• Implement validation checks, edge-case handling and data quality gates in CI/CD so pipelines are automated, observable and resilient
• Model data and optimize complex query performance across the warehouse and relational databases
• Provision and maintain infrastructure with Infrastructure as Code and keep deployment pipelines healthy
• Own data projects end-to-end: clarify requirements with stakeholders, make technical trade-offs, drive solutions to production and review code for other engineers

Nice-to-Haves

• Snowflake platform administration and FinOps: warehouse sizing, resource monitors, cost attribution and credit reduction
• Change Data Capture (CDC) pipelines from SQL Server or PostgreSQL into a cloud warehouse
• AI-native engineering: daily use of Claude Code, the Anthropic API or MCP servers to automate operational workflows
• Building compliance-ready data pipelines and reporting (e.g., SOC 2, HIPAA/HITRUST)
• Classification, NLP, entity resolution or fuzzy matching to map unstandardized datasets onto a core database
• Building internal tools, APIs (FastAPI, Django) or monitoring dashboards; experience with Pandas, DuckDB, Elasticsearch or Databricks
• AWS services such as ECS, Lambda, S3, RDS/Aurora, and VPC/IAM design
• BI and semantic-layer tools (Looker, Holistics, Tableau) or custom visualization frameworks (Vega-lite, d3)
• ML/AI-adjacent infrastructure (feature stores, training pipelines, model monitoring)
• Ruby / Ruby on Rails
• Certifications such as SnowPro Advanced (Administrator or Data Engineer) or AWS Certified Solutions Architect
• Background in financial services, healthcare or climate tech

Who You Are

• You are highly autonomous and comfortable self-directing solutions around ambiguous requirements and loose data formats
• You are a proactive communicator who flags risks, blockers and timelines early, and you translate business rules from stakeholders into technical solutions
• You take pride in clean, maintainable, well-documented code and give clear, actionable code review feedback
• You are rigorous and analytical, treating reliability, data quality and cost as measurable engineering goals
• You approach data anomalies and broken pipelines systematically and own the outcome through to the production fix