Data Engineer

Tata Consultancy Services; Charlotte (NC); On-site; USD 95,000 - 115,000; Full time

Job summary

Tata Consultancy Services in Charlotte, NC is seeking a Data Engineer to support production data pipelines and data platforms. You will work across Hadoop, Spark, and cloud-based data stores to ensure data readiness and reliable analytics.

The role emphasizes ETL/ELT development, performance tuning, and monitoring, with collaboration across engineering, product, and business teams to resolve issues and improve data quality.

Qualifications

• 5 to 10 years in Data Engineering or related field.
• Strong proficiency in Python and SQL for data transformations.
• Experience designing ETL/ELT pipelines and data ingestion processes.
• Hands-on experience with distributed data tools such as Apache Spark, Databricks, or Hadoop ecosystems.

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/GCP).
• 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

Skills

PySpark

Hive

Python

SQL

Hadoop

Unix

Agile

Base support

Job description

Job Description

Data engineer – Prod support

Must Have Technical/Functional Skills

• Primary Skill: PySpark, Hive, Python, SQL, Hadoop
• Secondary: Unix, Agile, Base support
• Experience: 5 to 10 years

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/GCP).
• 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

A Data Engineer is essential to implement efficient data flows, enforce data management standards, enhance data quality, and support continuous delivery and release cycles. Without this role, the project risks delays in data readiness, gaps in data compliance, reduced quality of analytical outputs, and inability to support downstream systems effectively.

Client is mainly looking for Production support ole to be able to root cause analysis of prod issues across different tech stack that we have(Hadoop, Oracle and MongoDB).Autosys knowledge, Analyze and fix performance issues, Dev work related to App Gov and other mandates.

Salary Range- $95,000-$115,000 a year