Senior Data Engineer
About The Position
This role is responsible for the design, development, and maintenance of data integration and reporting solutions. Working primarily in Databricks, you will build and maintain the pipelines and datasets that feed our reporting, analytics, and AI/ML workloads. The ideal candidate will possess expertise in Databricks and strong skills in SQL Server, SSIS and SSRS, and experience with other modern data engineering tools such as Azure Data Factory. This position requires a proactive and results-oriented individual with a passion for data and a strong understanding of data warehousing principles. A strong grasp of AI-assisted development tools as a regular part of the engineering workflow is expected.
Requirements
- Bachelor's Degree in Computer Science, Information Systems, or a related field.
- 7+ years of experience in data integration and reporting.
- Extensive experience with Databricks, including Python, Spark, and Delta Lake
- Experience with data warehousing concepts and best practices.
- Strong proficiency with AI-assisted development tools.
- Strong proficiency in SQL Server, including T-SQL, stored procedures, and functions.
- Experience with SSIS (SQL Server Integration Services) development and maintenance.
- Experience with SSRS (SQL Server Reporting Services) report design and development.
- Strong analytical and problem-solving skills.
- Excellent communication and interpersonal skills.
- Ability to work independently and as part of a team.
- Experience with Agile methodologies.
Nice To Haves
- Experience with other modern data engineering tools such as Azure Data Factory.
- Experience with Microsoft Azure cloud platform and Microsoft Fabric desirable.
Responsibilities
- Design, develop, and maintain robust and efficient ETL pipelines and processes on Databricks.
- Troubleshoot and resolve Databricks pipeline errors and performance issues.
- Troubleshoot and resolve SSIS package errors and performance issues.
- Optimize data flow performance and minimize data latency.
- Implement data quality checks and validations within ETL processes.
- Maintain legacy SSIS packages for ETL processes.
- Develop and maintain Databricks pipelines and datasets using Python, Spark and SQL.
- Drive the design and implementation of batch and streaming data lake architectures supporting both analytics and AI/ML workloads.
- Optimize Databricks jobs for performance and cost-effectiveness.
- Integrate Databricks with other data sources and systems.
- Migrate legacy systems (e.g. SSIS packages, SQL Server procs) to Databricks pipelines.
- Participate in the design and implementation of data warehousing.
- Support data quality initiatives and implement data cleansing procedures.
- Collaborate with business users to understand data requirements for department driven reporting needs.
- Maintain existing library of complex SSRS reports, dashboards, and visualizations.
- Troubleshoot and resolve SSRS report issues, including performance bottlenecks and data inconsistencies.
- Comfortable in entrepreneurial, self-starting, and fast-paced environment, working both independently and with our highly skilled teams.
- Collaborate effectively with business users, data analysts, and other IT teams.
- Communicate technical information clearly and concisely, both verbally and in writing.
- Document all development work and procedures thoroughly.
- Keep abreast of the latest advancements in data integration, reporting, data engineering.
- Actively contribute to company’s AI-assisted tooling, strategies, and best practices.
- Continuously improve skills and knowledge through training and self-learning.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
