Description

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

This role is remote.

Responsibilities

• Build and optimize batch and real-time streaming data pipelines using distributed processing frameworks.
• Design cloud-native data platforms and implement data warehouses, data lakes, and lakehouse architectures.
• Handle structured, semi-structured, and unstructured data using various file formats and NoSQL/relational databases.
• Implement CI/CD pipelines, DevOps practices, and infrastructure automation for data engineering workflows.
• Ensure data quality, governance, security, and observability across distributed systems.

Required Skills

• 4+ years of experience in data engineering, ETL/ELT workflows, and scalable data architectures.
• Proficiency in Python, SQL, PySpark, Spark SQL, and Scala.
• Experience with big data technologies including Apache Spark, Databricks, Hadoop, Airflow, and Kafka.
• Strong understanding of cloud platforms (AWS, Azure, or GCP) and services like S3, Glue, Redshift, or Azure Data Factory.
• Experience with database technologies such as PostgreSQL, MySQL, Oracle, MongoDB, Cassandra, and DynamoDB.
• Familiarity with CI/CD tools like GitLab CI/CD, Jenkins, or GitHub Actions.
• Knowledge of data modeling techniques including star schemas, snowflake schemas, and dimensional models.

Preferred Skills

• Experience with streaming technologies like Flink or Kinesis.
• Understanding of partitioning strategies and performance tuning for distributed systems.

Key Skills

Education

Bachelor's degree