Databricks Engineer

Role & responsibilities

• Developing Modern Data Warehouse solutions using Databricks and AWS/ Azure Stack
• Ability to provide solutions that are forward-thinking in data engineering and analytics space
• Collaborate with DW/BI leads to understand new ETL pipeline development requirements.
• Triage issues to find gaps in existing pipelines and fix the issues
• Work with business to understand the need in reporting layer and develop data model to fulfill reporting needs
• Help joiner team members to resolve issues and technical challenges.
• Drive technical discussion with client architect and team members
• Orchestrate the data pipelines in scheduler via Airflow

Preferred candidate profile

Must have total 6+ yrs. of IT experience and 3+ years' experience in Data warehouse/ETL projects.

Deep understanding of Star and Snowflake dimensional modelling.

Strong knowledge of Data Management principles

Good understanding of Databricks Data & AI platform and Databricks Delta Lake Architecture

Should have hands-on experience in SQL, Python and Spark (PySpark)

Candidate must have experience in AWS/ Azure stack

Desirable to have ETL with batch and streaming (Kinesis).

Experience in building ETL / data warehouse transformation processes

Experience with Apache Kafka for use with streaming data / event-based data

Experience with other Open-Source big data products Hadoop (incl. Hive, Pig, Impala)

Experience working in a Dev/Ops environment with tools such as Terraform, CircleCI, GIT.

Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot

Databricks Certified Data Engineer Associate/Professional Certification (Desirable).