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Gypsy Collective

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Middle DWH Engineer

Location

Ukraine

Posted

11 days ago

Salary

0

Seniority

Mid Level

Job Description

Middle DWH Engineer

Gypsy Collective

Role Description 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. - 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. Qualifications - 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). Requirements - 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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