Data Analytics Engineer

Welcome!

Responsibilities

• Design, develop, and maintain ETL (Extract, Transform, Load) pipelines for integrating data from multiple sources (databases, APIs, files, streaming, etc.).
• Build and optimize data pipelines to support both batch and real-time data processing.
• Collaborate closely with Data Analysts, Data Scientists, and business teams to deliver clean and reliable data.
• Manage and optimize data warehouse / data lake platforms (e.g., BigQuery, Snowflake, Redshift, Hadoop, Spark).
• Ensure data quality, consistency, and accuracy across systems.
• Develop scripts and automation tools to improve workflow efficiency and reduce manual work.
• Monitor, troubleshoot, and resolve issues in data pipelines and related infrastructure.
• Bachelor’s degree or higher in Computer Science, Information Technology, Data Engineering, or related fields.
• 2–3 years of experience in Data Engineering or ETL development.
• Strong experience in SQL (query optimization, stored procedures, complex joins).

Qualifications

• Hands-on experience with ETL/ELT tools such as Airflow, dbt, Talend, Informatica, SSIS, or custom Python scripts.
• Experience working with both relational databases (MySQL, PostgreSQL, SQL Server, Oracle) and NoSQL databases (MongoDB, Cassandra, DynamoDB).
• Familiarity with at least one cloud platform (AWS, GCP, Azure).
• Knowledge of data modeling, data warehousing, and data governance.
• Proficiency in Python/Scala/Java for data processing.
• Familiarity with Git, Docker, and CI/CD pipelines is a plus.
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