Data Engineer

Education & Experience

• Bachelor's degree, preferably in Engineering or Business.
• 6–9 years of professional experience designing, building, and supporting enterprise-scale data engineering or platform solutions.

Required Technical Expertise (Must Have)

• Strong hands-on experience building and maintaining ELT/ETL pipelines to move and transform data across heterogeneous data platforms, including Snowflake, Oracle, and PostgreSQL.
• Deep understanding of data structures, relational databases, and cloud-native storage technologies across Snowflake, Oracle, Postgres, and other cloud-based RDBMS platforms.
• Proficiency in Python and SQL, with practical experience using scripting languages such as Shell and Groovy for automation and data processing.
• Proven experience designing, implementing, and orchestrating complex data pipelines using Apache Airflow and/or Control?M, with a focus on scalability, reliability, and operational efficiency.
• Hands-on expertise with Docker, including container image creation, multi-stage builds, container registries, and secure, scalable container-based deployments.
• Strong experience implementing CI/CD pipelines using GitHub and Jenkins, including automated builds, testing, deployments, and adherence to security and quality procedures.

Cloud & Platform Experience

• Solid understanding of core AWS services, including Lambda, SQS/SNS, EC2, S3, CloudWatch, and IAM roles/policies, supporting data and application workloads in cloud environments.

Preferred / Nice to Have

• Exposure to modern front-end and application development technologies such as Angular, Node.js, and TypeScript.
• Experience working with additional cloud-native databases such as AWS DynamoDB.
• Familiarity with Go (Golang) for backend or data platform development.
• Broader experience supporting data solutions across PostgreSQL and AWS-based architectures.