What are the responsibilities and job description for the Applications Support Technical Lead - Data Analytics / Azure / Databricks position at MetaSense, Inc.?
Job Title: Applications Support Technical Lead - Data Analytics / Azure / Databricks
Location: Montvale, NJ ( Hybrid- 3 days per week onsite) | Locals only
Employment Type: Long Term Contract
Our client, a prestigious global firm, is seeking an experienced Applications Support Technical Lead for a long-term contract opportunity supporting global, Azure-based data analytics platforms.
This is a hands-on technical leadership position focused on complex incident resolution, data platform troubleshooting, large dataset support, and root-cause analysis across modern Azure data environments.
The right candidate will serve as an escalation lead for challenging production issues involving large datasets, data pipelines, performance bottlenecks, configuration problems, and data-processing failures. You will work closely with support analysts, engineering teams, and product stakeholders to diagnose issues, guide resolution, and help create durable fixes.
Key Responsibilities:
- Lead technical support and escalation for complex data analytics application issues
- Troubleshoot large-scale data processing problems involving volume, performance, data quality, configuration, and transformation logic
- Investigate issues across Azure data services, Databricks, PySpark, SQL Server/DWH, ADLS, Delta, and Parquet
- Diagnose ETL, reporting, dataset upload, and data movement issues across cloud-based platforms
- Use advanced T-SQL skills to analyze, tune, and resolve production data issues
- Create reusable troubleshooting assets, including runbooks, query packs, diagnostics, and support documentation
- Coach analysts and partner with engineering/product teams to drive root-cause closure
Required Experience:
- 8 years of experience in application support, technical lead, data platform support, or production troubleshooting roles
- Strong hands-on experience with Azure data engineering and Python
- Working knowledge of Databricks and PySpark
- Strong T-SQL / data warehouse background, including stored procedures, functions, execution plans, indexing, CTEs, temp tables, and performance tuning
- Experience troubleshooting large datasets, data pipelines, ETL workflows, and reporting issues
- Strong understanding of relational database concepts and modern data platform support
- Excellent communication skills with the ability to explain complex technical issues clearly
Nice to Have:
- Azure Data Factory experience
- ADLS file format expertise: Parquet/Delta vs. CSV/Excel
- Power BI, Alteryx, or advanced Excel
- MSBI / SSIS background
- ERP data experience with SAP or Oracle
- Basic accounting or financial dataset knowledge