Lead Data Engineer

In-depth working experience of distributed systems Hadoop, Spark, Hive, DBT and Airflow/Dagster

At least 5 years of solid production quality coding experience in data pipeline implementation in Python

Experience working with public cloud platforms, preferably AWS

Experience working with Databricks and/or Snowflake

Experience in Git, JIRA, Jenkins, shell scripting

Familiarity with Agile methodology, test-driven development, source control management and test automation

Experience supporting and working with cross-functional teams in a dynamic environment

You have excellent collaborative problem solving and communication skills and are empathetic to others

You have a track record of building fast, reliable, and high-quality data pipelines

Graduate in Computer Science, Data Science, Information Technology, or a related field. 

8+ years of experience and a bachelor’s degree in computer science or a related field, or equivalent work experience

Strong hands-on experience with PySpark, Python, SQL, Databricks, and AWS Cloud is required at a Lead level. The candidate should possess excellent problem-understanding and problem-solving capabilities, be able to lead technical discussions, guide team members, and effectively communicate and collaborate with both internal teams and client stakeholders.

You will build services that will integrate directly with Client's products and with external vendors.

You will work with modern data technologies such as Hadoop, Spark, DBT, Dagster/Airflow, Atlan, Trino, etc., modern data platforms such as Databricks and Snowflake and cloud technologies across AWS stack

Identify, design, and implement automation of manual processes, optimizing data delivery, reducing Cloud cost, etc.

Implement processes and systems to monitor Data Quality, Observability, Governance and Lineage.

Support operations to manage the production environment and help in resolving production issues with RCA

Write unit/integration tests, adopt Test-driven development, contribute to engineering wiki, and document design/implementation etc.