Senior Engineer – Data Engineering, Databricks
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Job Description
Senior Databricks data engineer building scalable batch and streaming lakehouse pipelines. Delivering data platforms and solution accelerators for Slalom consulting clients.
Responsibilities:
- Provide technical leadership with minimal oversight to deliver innovative solutions on the Databricks Platform
- Use cloud data lakehouse methodologies, distributed processing engines, event streaming platforms, and modern data technologies
- Participate in the Databricks Center of Excellence
- Build next-generation data platforms for organizations in data and analytics
- Work under a Solution Architect to design and implement components of client data platform solutions
- Participate in design sessions, break down complex development tasks, and complete development items on time
- Contribute to Center of Excellence initiatives by developing Databricks solution accelerators
- Develop and implement data solutions using Databricks
- Collaborate with cross-functional teams to design and optimize batch and streaming data pipelines
- Ensure data quality and efficiency
- Stay current with emerging technologies and Databricks platform features and continuously improve relevant skills
Requirements:
- 5+ years of data engineering experience
- At least 2 years of hands-on data pipeline design and development experience with Databricks
- Experience with Delta Lake, Uniform (Iceberg), Delta Live Tables (Lakeflow Declarative Pipelines), and Unity Catalog
- Proficiency designing and building scalable YAML configuration-driven data pipelines
- Experience with batch, micro-batch, and streaming data ingestion and processing patterns using tools such as Auto Loader
- Experience building complex job/workflow orchestration patterns using Databricks Jobs/Workflows or tools such as Airflow and dbt
- Exposure to data quality, pipeline audit, and observability solutions using Databricks native features or tools/frameworks such as Great Expectations, Collibra, and dbt
- Proficiency with Apache Spark, Presto, and Amazon EMR
- Experience with Amazon Redshift, Snowflake, and Google BigQuery
- Strong programming skills in SQL, stored procedures, and object-oriented programming languages such as Java, Python, and PySpark
- Familiarity with DevOps and CI/CD pipelines using Databricks Asset Bundles, including automated validation and testing
- Exposure to Infrastructure as Code tools such as Terraform is a plus
- Familiarity with NoSQL databases and container management systems
- Exposure to AI/ML tools such as MLflow, prompt engineering, and modern data and AI agentic workflows
- Databricks Data Engineering Associate and/or Professional certification is ideal
- Multiple Databricks project delivery experience
- Curious, self-starting mindset and ability to share insights with teams
Benefits:
- Contract engagement for 6+ months
- Start date in Dec/Jan
- Remote work arrangement
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