Data Engineer

Helic Co — United Kingdom · Posted ~2 hours ago

Remote

Skills

Data engineering ETL/ELT Data pipelines Data architecture Data warehouses Data lakes Data modeling SQL Data quality Data security Pipeline monitoring Data governance Batch processing Real-time data processing ETL ELT

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Summary ✨ AI‑Generated

Work remotely as a Data Engineer designing and maintaining scalable data infrastructure and ETL/ELT pipelines. You will build data warehouses and lakes, develop robust data models, optimize SQL and large datasets, ensure data quality and security, monitor pipelines, and support both batch and real-time processing.

Highlights

Fully remote data engineering work focused on scalable pipelines, modern data architectures, data quality, governance, and reliable analytics infrastructure. The role spans batch and real-time processing and offers collaboration with analysts, data scientists, and software engineers.

Description

This is a remote position. Job Summary We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data infrastructure and pipelines. In this role, you will be responsible for ensuring reliable data flow, optimizing data systems, and enabling analytics and business intelligence across the organization. Key Responsibilities Design, develop, and maintain scalable data pipelines (ETL/ELT processes) Build and optimize data architectures, including data warehouses and data lakes Develop and maintain robust data models to support analytics and reporting Write efficient SQL queries and manage large datasets Ensure data quality, integrity, and security across systems Monitor and troubleshoot data pipeline performance issues Collaborate with data analysts, data scientists, and software engineers Implement data governance and best practices Support real-time and batch data processing solutions Qualifications Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field Strong proficiency in SQL and database technologies Experience with programming languages such as Python, Java, or Scala Hands-on experience with data pipeline tools (e.g., Apache Airflow, Kafka) Familiarity with cloud platforms (AWS, Azure, Google Cloud) Understanding of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) Strong problem-solving and analytical skills Preferred Skills Experience with big data technologies (e.g., Hadoop, Spark) Knowledge of data modeling techniques and schema design Familiarity with containerization tools (Docker, Kubernetes) Experience with CI/CD pipelines and DevOps practices Understanding of data security and compliance standards