A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role you'll be encouraged to challenge the norm investigate ideas outside of your role and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
Role Overview
We are looking for a Data Engineer with strong hands-on Databricks experience who will design and optimize scalable data pipelines work with Delta Lakehouse architectures and enable advanced analytics across Azure or AWS platforms.
Key Responsibilities
- Develop ETL/ELT pipelines in Databricks using PySpark Spark SQL Delta Lake .
- Use Delta Live Tables for simplified pipeline orchestration.
- Implement Databricks Auto Loader for real-time/batch data ingestion.
- Build Databricks SQL dashboards and queries for reporting and analytics.
- Manage Databricks clusters jobs and workflows ensuring cost efficiency.
- Work with cloud-native services ( ADF Synapse ADLS or AWS Glue S3 Redshift ) for data integration.
- Apply Unity Catalog for role-based access and lineage tracking.
- Collaborate with data scientists to support ML workloads using MLflow .
Mandatory Skills
- Strong Databricks expertise : PySpark Spark SQL Delta Lake (ACID schema evolution time travel).
- Exposure to Delta Live Tables Auto Loader Unity Catalog MLflow .
- Hands-on with Azure or AWS data services .
- Strong SQL and Python programming for data pipelines.
- Knowledge of data modeling (star/snowflake lakehouse) .
Good to Have
- Streaming data experience (Kafka Event Hub Kinesis).
- Familiarity with Databricks REST APIs .
- Certification: Databricks Data Engineer Associate Azure DP-203 / AWS Analytics Specialty.