Join our dynamic team as a Technical Leader in Software Engineering. This role focuses on designing and developing robust data solutions leveraging cutting-edge technologies in Big Data and Cloud platforms. You will be instrumental in building scalable and efficient data pipelines, ensuring seamless integration and deployment processes.

This is an excellent opportunity to lead critical projects, contribute to architectural decisions, and mentor junior team members. If you are passionate about data, possess strong technical acumen, and thrive in a collaborative environment, we encourage you to apply.

Design and implement scalable batch and near-real-time ETL/ELT data pipelines utilizing Snowflake (AWS) and Apache Spark (PySpark, Spark SQL, Structured Streaming). Build advanced structured streaming pipelines integrating Kafka and Spark Structured Streaming. Develop dimensional data models, including Fact/Dimension tables and SCD Type 2 implementations. Orchestrate complex data workflows using Databricks Workflows or Apache Airflow. Establish and maintain CI/CD integration through Jenkins and Git (Bitbucket/GitHub) for automated deployments across development, UAT, and production environments.

A minimum of 6 to 8 years of professional experience in software development, with a strong focus on data engineering. Proficiency in core technologies such as Apache Spark (Core, Structured Streaming), PySpark, Databricks (AWS/Azure), and Advanced SQL. Solid experience with DevOps tools like Jenkins and version control systems including Git, GitHub, or Bitbucket. Hands-on programming skills in Python and SQL. Familiarity with cloud platforms, particularly AWS services like S3, EMR, EC2, IAM, and CloudWatch. Experience with streaming technologies like Apache Kafka. Preferred qualifications include experience in financial services, payouts, or enterprise data platforms, Delta Lake optimization, Snowflake data warehousing, and a strong grasp of distributed computing principles.