Companies Gypsy Collective Middle DWH Engineer

About the role

Gypsy Collective

We are looking for a Middle DWH Engineer to design, build, and maintain scalable data warehouse solutions that support analytics and business decision-making. You will work across the full data lifecycle - from data ingestion and transformation to orchestration and optimization - while collaborating with analysts, engineers, and business stakeholders.

📅  Your adventures include:

  • design, develop, and maintain DWH and Data Lake solutions aligned with business requirements;
  • build, optimize, and support ETL/ELT pipelines using Python, SQL, Airflow, and related technologies;
  • integrate and maintain data flows from APIs, databases, SaaS platforms, and third-party systems;
  • work with PostgreSQL, Trino, and cloud-based analytical platforms to support reporting and analytics needs;
  • implement and support incremental loading, CDC processes, backfills, and reprocessing workflows;
  • monitor, troubleshoot, and improve data pipelines to ensure reliability, stability, and timely delivery of data;
  • implement data quality checks, validation rules, and automated monitoring processes;
  • optimize SQL queries, data models, and pipeline performance;
  • collaborate with analysts, BI developers, engineers, and business stakeholders to deliver scalable data solutions;
  • participate in code reviews and contribute to engineering standards and best practices.

Requirements

🧭 What makes you a great match:

  • strong SQL skills, including complex queries, CTEs, window functions, analytical queries, and query optimization (3+ years);
  • strong experience integrating external data sources, including REST APIs, databases, SaaS platforms, and third-party systems; ability to design, develop, troubleshoot, and maintain reliable data ingestion processes in production environments (3+ years);
  • experience with Apache Airflow or similar workflow orchestration tools (3+ years);
  • experience with Python for data processing, integrations, and automation (2+ years);
  • good understanding of DWH concepts, including ETL/ELT, dimensional modeling, Data Vault, and Star/Snowflake schemas (3+ years);
  • experience building and supporting production data pipelines with a focus on reliability, stability, monitoring, and error handling;
  • understanding of data quality principles, including validation, testing, reconciliation, and monitoring;
  • hands-on experience with PostgreSQL and Trino in production environments;
  • experience with modern analytical databases or cloud data warehouses (such as BigQuery, Snowflake, Redshift, ClickHouse, Vertica, Athena, or similar platforms.);
  • experience with Git and collaborative development workflows (pull requests, code reviews, rebasing, merge conflict resolution).

⭐ Nice to Have

  • experience with Change Data Capture (CDC) tools and incremental loading strategies;
  • experience with cloud platforms such as AWS, GCP, or Azure;
  • familiarity with Docker and containerized environments;
  • experience with streaming or near real-time data pipelines (Kafka);
  • familiarity with dbt or similar data transformation frameworks;
  • experience with data cataloging, lineage, or governance tools.

Benefits

  • 💸 Flexible payment options: choose the method that works best for you.
  • 🧾 Tax assistance included: we handle part of your taxes and provide guidance on the local setup.
  • 🎁 Financial perks: Bonuses for holidays, B-day, work milestones and more - just to show we care.
  • 📈 Learn & grow: We cover courses and certifications — and offer real opportunities to grow your career with us.
  • 🥐 Benefit Сafeteria: Choose what suits you — sports, language courses, therapy sessions, and more.
  • 🎉 Stay connected: From team-building events to industry conferences — we bring people together online, offline, and on stage.
  • 💻 Modern Equipment: We provide new laptops along with essential peripherals like monitors and headphones for a comfortable workflow.
  • 🕘 Your schedule, your rules: Start your day at 9, 10, or even 11 — we care about results, not clock-ins.
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