Data Engineer

Cognitech is seeking a skilled Data Engineer to design, develop, test, and maintain scalable data pipelines and data processing solutions. The ideal candidate should have strong knowledge of Python, SQL, ETL/ELT processes, data modeling, data warehousing, and cloud-based data technologies.

The candidate will work with data analysts, data scientists, software engineers, and business teams to collect, transform, validate, and organize data from multiple sources. Responsibilities include building reliable data pipelines, improving data quality, optimizing SQL queries, automating data workflows, and ensuring that data is accurate, accessible, and ready for analytics and reporting.

The role may involve working with large datasets, distributed processing frameworks, cloud data platforms, and workflow orchestration tools. The candidate should be able to troubleshoot pipeline failures, document data processes, and contribute to scalable data architecture.

• Master’s degree in Computer Science, Data Engineering, Data Science, Information Technology, or a related field.

• 2–5+ years of experience in data engineering, data integration, or a related role.

• Strong programming knowledge in Python and SQL.

• Experience developing ETL/ELT pipelines and data transformation workflows.

• Knowledge of relational databases, data modeling, and data warehousing.

• Familiarity with Apache Spark, PySpark, Databricks, or similar processing technologies.

• Experience with Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.

• Knowledge of AWS, Azure, or Google Cloud Platform.

• Familiarity with data validation, data quality checks, and workflow automation.

• Experience with Git, debugging, documentation, and troubleshooting.

• Strong analytical, communication, and problem-solving skills.