Description

You will design, develop, and maintain scalable data pipelines and enterprise-grade data integration solutions.

This role is remote.

Responsibilities

• Build and optimize batch and real-time streaming data pipelines using distributed processing frameworks.
• Develop cloud-native data solutions on AWS, Azure, or GCP, leveraging services like S3, Glue, Redshift, and EMR.
• Implement CI/CD pipelines and DevOps practices using Git, Jenkins, and GitHub Actions for automation.
• Design data warehousing architectures, including dimensional modeling and Lakehouse patterns, for enterprise reporting.
• Optimize performance for relational and NoSQL databases, ensuring data quality and efficient query execution.

Required Skills

• 5+ years of experience in data engineering, ETL/ELT workflows, and large-scale data platforms.
• Strong proficiency in Python, SQL, PySpark, Spark SQL, and Scala.
• Hands-on experience with Apache Spark, Databricks, Hadoop, Airflow, and Kafka.
• Deep knowledge of cloud platforms (AWS/Azure/GCP) and their data services.
• Experience with relational and NoSQL databases including PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, Cassandra, and DynamoDB.
• Proficiency in CI/CD tools such as Jenkins, GitHub Actions, and Azure DevOps.
• Understanding of structured, semi-structured, and unstructured data formats (Parquet, Avro, JSON).

Preferred Skills

• Experience with event-driven architectures and microservices integration.
• Familiarity with streaming technologies like Apache Flink or Kinesis.
• Knowledge of data quality validation and monitoring tools.

Key Skills

Education

Bachelor's degree