Engineer

Tata Consultancy Services; Irving (TX); On-site; USD 90,000 - 110,000; Full time

Benefits offered by this job

Discretionary Annual Incentive.

Comprehensive Medical Coverage

401K Plan

Certification & Training Reimbursement

Job summary

Tata Consultancy Services is seeking a Data Engineer to design, build, and optimize scalable data pipelines using Spark, PySpark, and Hive in a cloud environment, delivering reliable and fast data for analytics.

You will manage ETL/ELT workflows, tune Spark jobs, oversee cloud infrastructure across AWS, Azure, or GCP, and collaborate with data scientists and analysts to translate business needs into robust data solutions.

Qualifications

• Proficient in Apache Spark architecture and DAGs.
• Strong Python and PySpark programming skills.
• Expert in HiveQL and ANSI SQL with partitioning.
• Experience with Parquet, ORC, Avro formats.
• Cloud data infrastructure on AWS/Azure/GCP.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using PySpark and Spark SQL.
• Manage cloud data infrastructure on AWS, Azure, or GCP.
• Optimize data warehousing and storage in Hive and data lakes.
• Tune Spark jobs and address data skew and memory usage.
• Ingest high-volume diverse datasets from relational and flat files.
• Coordinate data workflows using Airflow or platform schedulers.
• Collaborate with data scientists and analysts to translate requirements into data solutions.

Skills

Spark architecture

Python / PySpark

HiveQL / ANSI SQL

Parquet/ORC/Avro

Cloud data infrastructure

Dimensional modeling

Education

Bachelor of Computer Science

Tools

Apache Airflow

AWS EMR

Azure Databricks

Git

Jenkins

Ansible

Job description

Job Description

We are seeking a highly skilled and motivated Data Engineer to play a pivotal role in designing, building, and optimizing our next-generation scalable data pipelines. This position requires expertise in processing massive datasets using cutting-edge technologies like Apache Spark, PySpark, and Hive within a dynamic cloud environment. Your primary objective will be to ensure the utmost data reliability, speed, and efficiency, providing a robust foundation for downstream business intelligence and advanced analytics initiatives.

Roles & Responsibilities

• Data Pipeline Development & Maintenance: Design, build, and maintain highly scalable and efficient ETL/ELT data pipelines utilizing PySpark and Spark SQL for complex data transformations.
• Cloud Data Infrastructure Management: Deploy, manage, and scale critical data infrastructure components on leading cloud platforms such as Amazon Web Services (AWS) (e.g., EMR, Glue), Microsoft Azure (e.g., Databricks, Synapse), or Google Cloud Platform (GCP).
• Data Warehousing & Storage Optimization: Strategically manage data layout, partitioning, and indexing within Apache Hive and various cloud data lake solutions to optimize performance and accessibility.
• Performance Tuning & Optimization: Proactively identify and resolve performance bottlenecks in Spark jobs, leveraging Spark UI for in-depth analysis, effectively managing data skewness, and optimizing memory utilization.
• Diverse Data Integration: Develop robust solutions for ingesting high-volume and diverse datasets from both structured relational databases and unstructured flat files into our data ecosystem.
• Automated Workflow Orchestration: Implement and manage automated data workflows using industry-standard scheduling tools like Apache Airflow or platform-native schedulers, ensuring timely and reliable data delivery.
• Strategic Collaboration: Partner closely with data scientists, business analysts, and cross-functional enterprise teams to translate complex business requirements into technically sound and efficient data solutions.

Qualifications

• Big Data Frameworks Expertise: Demonstrated high proficiency in Apache Spark architecture, including a deep understanding of drivers, executors, and Directed Acyclic Graphs (DAGs).
• Advanced Programming: Exceptional coding skills in Python and extensive experience with the PySpark API for developing intricate data transformations and processing logic.
• Querying & Schema Management: Strong command of HiveQL and ANSI SQL, coupled with expertise in data partitioning techniques and effective schema definition.
• Optimized Storage Formats: In-depth understanding and practical experience with optimized big data storage file formats such as Parquet, ORC, and Avro.
• Cloud Ecosystem Development: Hands-on development experience utilizing cloud-native big data utilities (e.g., AWS EMR, Azure Databricks) within major cloud platforms.
• Data Warehousing Fundamentals: Solid foundation in Dimensional Data Modeling, including Star and Snowflake schemas, and practical experience with Data Lakes concepts and implementation.

Preferred Qualifications

• CI/CD & DevOps Automation: Experience with Continuous Integration/Continuous Deployment (CI/CD) practices and automation tools like Git , Jenkins, or Ansible.
• NoSQL Database Integration: Exposure to and experience with NoSQL databases such as HBase, Cassandra, or MongoDB.
• Professional Cloud Certifications: Relevant professional cloud certifications (e.g., AWS Certified Data Engineer, Microsoft Certified: Azure Data Engineer Associate) are highly valued

TCS Employee Benefits Summary

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
• Salary Range: $90,000 - 110,000 a year

BACHELOR OF COMPUTER SCIENCE