Technical Architect

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:

o optimized file management o Z-Ordering o 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.

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., * 10-13 years of hands-on experience in Big Data engineering.

• Expert skills in:

o PySpark - dataframe optimizations, partitioning, broadcast strategies, distributed computing. o Kafka - producer/consumer design, schema registry, streaming ETLs. o Hadoop ecosystem - HDFS, YARN, MapReduce/Tez, Oozie/Airflow. o Hive - advanced query tuning, TEZ optimization, partition/bucket management.

• Extensive hands-on experience with Databricks Lakehouse, including:

o Bronze/Silver/Gold layer modeling o Delta Lake optimizations o Data quality frameworks on Lakehouse o 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)., Qualifications : BACHELOR OF COMPUTER SCIENCE

Pulled from the full job description

• Pet insurance
• Health insurance
• Vision insurance
• Dental insurance
• Commuter assistance, 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- 125,000 a year