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A leading company is seeking a Data Engineer to design and optimize scalable data pipelines and workflows using Databricks. The role requires proficiency in Databricks, Spark, and Delta Lake, along with strong skills in Python and SQL. The engineer will ensure data reliability and performance while collaborating with stakeholders. This position offers an opportunity to work on cutting-edge data solutions and contribute to the company's data strategy.
We are looking for a Data Engineer who is certified in Databricks (required) to join our team. In this role you will be designing, developing, and optimizing scalable data pipelines and workflows on Databricks. The engineer will work closely with stakeholders to make certain data reliability, performance, and alignment with business requirements.
Scope of Work
Data Pipeline Development:
Data Optimization:
Data Integration:
Real-Time Streaming:
Data Quality and Governance:
Collaboration and Documentation:
Responsibilities
Fully functional and documented data pipelines.
Optimized and scalable data workflows on Databricks.
Real-time streaming solutions integrated with downstream systems.
Detailed documentation for implemented solutions and best practices.
Skills and Qualifications
Proficiency in Databricks(certified), Spark, and Delta Lake.
Strong experience with Python, SQL, and ETL/ELT development.
Familiarity with real-time data processing and streaming.
Knowledge of cloud platforms (e.g., AWS, Azure, GCP).
Experience with data governance and tools like Unity CatLog.
Assumptions
Access to necessary datasets and cloud infrastructure will be provided.
Timely input and feedback from stakeholders.
Success Metrics
Data pipelines deliver accurate and consistent data.
Workflows meet performance benchmarks.
Real-time streaming solutions operate with minimal latency.
Stakeholders are satisfied with the quality and usability of the solutions.