Data Architecture & Modeling: Apply relational, dimensional, and data-warehouse modeling principles to build scalable and maintainable data solutions.
Production Support & Troubleshooting: Analyze failed jobs, data-quality issues, performance problems, and production incidents; perform root-cause analysis and implement sustainable resolutions.
Job Scheduling & Automation: Develop and support enterprise batch-processing workflows using scheduling/orchestration platforms such as AutoSys.
Big Data Platforms: Work with Hadoop ecosystem technologies including HDFS, Hive and related distributed-processing technologies.
Data Quality & Reconciliation: Implement validation, reconciliation, exception handling, logging, monitoring, and data-quality controls within data pipelines.
Code Quality: Participate in code reviews and enforce development standards for SQL, Python/PySpark, ETL, and data-processing components.
DevOps: Use Git-based source control and participate in CI/CD processes; work with container technologies such as Docker/Kubernetes where applicable.
Security: Follow secure data-development practices, access-control requirements, encryption standards, and organizational security policies.
Technical Collaboration: Work closely with application developers, infrastructure teams, business teams, and other technology groups to design and deliver solutions.
Continuous Improvement & AI: Evaluate new technologies and leverage approved AI-assisted development tools to improve code quality, troubleshooting, refactoring, and developer productivity.
Appropriately assess risk when business decisions are made, demonstrating consideration for the firm’s reputation and safeguarding the firm, its clients, and assets while complying with applicable laws, rules, regulations, and policies.
Recommended Qualifications
8+ years of relevant experience in data engineering, application development, database development, or related technology roles.
Strong hands-on experience with Python and PySpark for large-scale data processing and ETL development.
Strong proficiency in SQL/T-SQL and relational database technologies, preferably Microsoft SQL Server.
Experience developing and supporting complex SQL queries, stored procedures, database objects, and high-volume data-processing solutions.
Strong understanding of SQL Server performance tuning, including query execution plans, indexing, statistics, joins, locking/blocking, and query optimization.
Experience with Microsoft BI/SSIS or comparable enterprise ETL technologies.
Experience working with large datasets and distributed data platforms such as Hadoop/HDFS/Hive.
Strong understanding of ETL architecture, data warehousing, dimensional modeling, and relational/3NF modeling.
Experience implementing data-quality checks, reconciliation, audit controls, exception handling, and production monitoring.
Experience with enterprise scheduling/orchestration tools such as AutoSys.
Experience with Git, CI/CD, and modern development practices.
Familiarity with Docker/Kubernetes is preferred.
Familiarity with NoSQL technologies such as MongoDB is beneficial.
Strong analytical, troubleshooting, communication, and problem-solving skills.
Ability to work independently on complex technical assignments while collaborating effectively across teams.
Experience mentoring or providing technical guidance to other developers
Education
Bachelor’s degree/University degree or equivalent experience.
Job Family Group
Technology
Job Family
Applications Development
Time Type
Full time
- Most Relevant Skills
- Please see the requirements listed above.
- Other Relevant Skills
- For complementary skills, please see above and/or contact the recruiter.
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