Short description:  

We’re looking for a Data Engineer to help us build and optimize the data infrastructure behind our products and client solutions. You’ll design, orchestrate, and maintain reliable data pipelines that move data from diverse sources (databases, REST APIs, files, and third-party services) into well-modeled, analytics-ready data warehouses and data lakes. You’ll collaborate closely with software engineers, data analysts, and product teams to make sure data is accurate, available, secure, and delivered on time to the people and systems that rely on it.

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Key Responsibilities:

• Design, develop, and maintain scalable, well-orchestrated batch and streaming data pipelines

• Build ETL/ELT processes to integrate data from multiple sources (databases, APIs, and files) into data warehouses and data lakes

• Model data and design schemas that support analytics, reporting, and product features, and deliver curated datasets to downstream consumers

• Ensure data quality, integrity, and compliance with data governance best practices

• Optimize query performance, storage, memory use, and processing for large datasets

• Implement automation, monitoring, and alerting to improve pipeline reliability

• Maintain code quality and repeatable, automated releases of data workflows through testing and CI/CD

• Collaborate with product, analytics, and engineering teams to translate requirements into data solutions

• Document data flows, models, and processes clearly for the wider team

• Stay up to date with emerging trends in data engineering and cloud technologies

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Requirements:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

• 3+ years of experience in data engineering or a related role

• Advanced proficiency in SQL and Python

• Proven experience building data pipelines, ETL/ELT processes, and cloud-based data solutions

• Hands-on experience with cloud data platforms, preferably AWS (S3, RDS, MWAA) or equivalents on Azure (Data Lake Storage, Synapse/Fabric, Data Factory) or GCP (Cloud Storage, BigQuery)

• Experience with orchestration tools such as Apache Airflow or equivalents like Azure Data Factory, Dagster, or Prefect

• Experience with Python data processing (pandas, PyArrow) or equivalents such as Polars, DuckDB, or Apache Spark (e.g., on Databricks)

• Solid understanding of data warehousing, data lakes, and data modeling, with hands-on use of PostgreSQL or SQL Server (or MySQL, Azure SQL)

• Experience integrating data via REST APIs (or GraphQL, SOAP) and working with formats such as Parquet, JSON, and CSV/Excel

• Proficiency with Git and CI/CD for data workflows (e.g., GitHub Actions, Azure DevOps), including automated testing and code-quality checks

• Strong problem-solving and communication skills

• Excellent command of English language both written and oral

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Nice to have:

• Relevant cloud certifications (e.g., AWS Certified Data Engineer – Associate, Azure Data Engineer Associate, or Google Professional Data Engineer)

• Experience with streaming technologies such as Kafka, Amazon Kinesis, or Azure Stream Analytics

• Experience with dbt, Snowflake, or similar modern data stack tools (e.g., SQLMesh, BigQuery, Amazon Redshift)

• Familiarity with containerization and orchestration (Docker or Podman; Kubernetes, Amazon ECS, or Azure Container Apps)

• Knowledge of data visualization and BI tools such as Metabase, Power BI, or Tableau

• Experience in Agile and/or Scrum

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Working at Galeyo:

We believe careers are more than titles like Junior, Medior, or Senior. At Galeyo, growth is not a checklist - it’s a journey of learning, impact, and personal evolution. The Galeyo Club reflects that philosophy.  

From Rising Star to Ambassador, your path here is shaped by what you contribute, how you grow, and the difference you make - not just how long you’ve been here. Every phase brings new opportunities, recognition, and ways to create something that matters - for yourself, for others, and for Galeyo.