Technical Architect

Tata Consultancy Services; Plano (TX); On-site; USD 110,000 - 130,000; Full time

Benefits offered by this job

Annual incentive

Medical coverage

Parental leaves

Insurance options

Training reimbursement

Time off

Legal assistance

401K plan

Job summary

Tata Consultancy Services in Plano, TX is seeking a Senior Big Data Engineer with 10–13 years of hands-on experience to design and optimize large-scale data solutions for financial services.

The role requires expert PySpark, Kafka, Hadoop ecosystem, Hive, and Databricks Lakehouse architecture, including Bronze/Silver/Gold modeling, Delta Lake, and scalable pipelines. You will collaborate with quants, risk teams, and architects to deliver governed data platforms.

Qualifications

• 10–13 years of hands-on Big Data engineering experience.
• Expert skills in PySpark, Kafka, Hadoop ecosystem, Hive, and Databricks Lakehouse.
• Strong SQL knowledge on TB/PB-scale datasets and data modeling.

Responsibilities

• Design, develop, and optimize PySpark ETL pipelines on on-prem Hadoop clusters and cloud environments.
• Build high-volume ingestion frameworks using Kafka for real-time data.
• Tune Hadoop ecosystem components (HDFS, YARN, MapReduce/Tez, Oozie/Airflow).
• Build Hive data models for regulatory reporting and risk processing.
• Architect Bronze/Silver/Gold layer modeling in Databricks Lakehouse.

Skills

PySpark

Apache Kafka

Hadoop ecosystem

Hive

Databricks Lakehouse

Delta Lake

Big Data ETL

SQL

Git

Jenkins

Bitbucket

Real-time ingestion

Data governance

Cloud & on-prem platforms

Education

Bachelor of Computer Science

Tools

Oozie/Airflow

YARN

HDFS

MapReduce/Tez

Job description

Job Description

Must Have Technical/Functional Skills

Primary skills: PySpark, Apache Kafka, Hadoop Ecosystem, Hive, Databricks Lakehouse Architecture, Delta Lake, Bronze/Silver/Gold Data Modeling, Big Data ETL Pipeline Development, SQL, Real-time Data Ingestion Frameworks, Data Governance & Cataloging, CI/CD Tools – Git, Jenkins, Bitbucket, Workflow Orchestration, and Cloud & On-Prem Big Data Platforms.

Experience: Minimum 10+ years

Roles & Responsibilities

Seeking a Senior Big Data Engineer with 10–13 years of experience specializing in Hadoop, PySpark, Kafka, Hive, and strong experience designing data solutions for large-scale financial systems.

In addition, the candidate must possess advanced expertise in Databricks Lakehouse architecture, particularly around Bronze/Silver/Gold layer data modeling, Delta Lake optimizations, and building reliable, scalable pipelines for regulatory, risk, trading, and analytics workloads.

This role focuses on delivering highly performant, well-governed data platforms that support the bank’s mission‑critical global markets functions.

Key Responsibilities

Big Data Platform Engineering

• Design, develop, and optimize PySpark-based ETL pipelines running on on‑prem Hadoop clusters and cloud environments.
• Build high‑volume ingestion frameworks using Kafka for real‑time and near‑real‑time trading and market data.
• Develop, tune, and manage Hadoop ecosystem components—HDFS, YARN, MapReduce, Tez, Oozie/Airflow.
• Build high‑performance, optimized Hive data models for regulatory reporting, trade lifecycle, and market risk processing.

Databricks Lakehouse & Delta Framework

• Architect and implement Bronze/Silver/Gold layer modeling patterns within the Databricks Lakehouse.
• Apply Delta Lake best practices including:
  • optimized file management
  • Z-Ordering
  • Delta Change Data Feed (CDF) o schema evolution & enforcement o ACID transaction handling
• Build reusable frameworks for ingestion, cleansing, transformation, and consumption of data across Lakehouse layers.
• Enable governance, lineage, and auditability using Unity Catalog or equivalent cataloging tools.

Collaboration, Leadership & Delivery

• Collaborate closely with quants, product owners, architects, risk tech, and business users.
• Participate in agile ceremonies — sprint planning, refinement, design reviews.
• Mentor junior engineers and contribute to building strong engineering practices across tech teams.

Required Skills & Experience

• 10–13 years of hands‑on experience in Big Data engineering.
• Expert skills in:
  • PySpark — dataframe optimizations, partitioning, broadcast strategies, distributed computing.
  • Kafka — producer/consumer design, schema registry, streaming ETLs.
  • Hadoop ecosystem — HDFS, YARN, MapReduce/Tez, Oozie/Airflow.
  • Hive — advanced query tuning, TEZ optimization, partition/bucket management.
  • Extensive hands‑on experience with Databricks Lakehouse, including:
    • Bronze/Silver/Gold layer modeling
    • Delta Lake optimizations
    • Data quality frameworks on Lakehouse
    • Structured & unstructured data handling
    • Experience in Global Markets, Risk, Treasury, Trade Surveillance, or Regulatory Reporting.
  • Strong SQL knowledge with experience working on massive datasets (TB/PB scale).
• Experience with CI/CD practices — Git, Jenkins, Bitbucket, build pipelines.

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: $110,000- 130,000 a year

Qualifications:

BACHELOR OF COMPUTER SCIENCE