Data engineer Production Support

Job Description:

Job Title: Data engineer Production Support

Experience: 5 to 10 years

Location: Charlotte, NC, Addison, TX

Employment Type: Full Time
Work Model: Onsite

Must Have Technical/Functional Skills

Primary Skill: PySpark, Hive, Python, SQL, Hadoop

Secondary: Unix, Agile, Base support

Desired Skills : Hadoop

Job Summary:

We are seeking a highly motivated Data Engineer - Production Support to join our data engineering team. This role is primarily focused on supporting and maintaining critical production data platforms, ensuring system stability, resolving complex production issues, and driving continuous improvements across the data ecosystem.

The ideal candidate will possess strong expertise in PySpark, Python, SQL, Hive, and Hadoop, along with hands-on experience in production support, troubleshooting, performance tuning, and root cause analysis. The candidate will work across multiple technologies including Hadoop, Oracle, MongoDB, Unix/Linux, and Autosys to support business-critical applications and data pipelines.

Roles & Responsibilities:

• 5 to 10 years of experience in Data Engineering, Software Engineering, or related technical discipline.
• Strong proficiency in Python, and SQL for advanced data transformations.
• Hands-on experience designing and building ETL/ELT pipelines, data ingestion processes, and distributed data processing jobs.
• Practical experience working with distributed data tools such as Apache Spark, Databricks, or Hadoop ecosystems.
• Experience building and managing datasets in relational and/or cloud based data platforms (Teradata, Snowflake, SQL Server, Azure/AWS/Google Cloud Platform).
• Solid understanding of data modeling, metadata, data quality controls, data lineage, and secure data management.
• Experience contributing to automated test suites, analyzing test failures, and supporting test-driven development.
• Knowledge of CI/CD pipelines, version control (Git), and automated deployment practices.
• Experience adhering to enterprise data governance, compliance, and operational risk frameworks.
• Ability to troubleshoot pipeline issues, performance bottlenecks, and data discrepancies.
• Strong communication skills and ability to collaborate across engineering, product, and business teams.
• Experience implementing monitoring and observability for data pipelines (logs, metrics, health checks).
• Advanced experience with performance tuning of SQL, Spark, or distributed data workflows.
• Knowledge of data security practices (encryption, masking, PII handling).
• Experience supporting analytical workloads, BI tools, or data science teams.

Prior experience in a financial institution or other regulated industry