Big Data Developer

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Role Overview

We are looking for a Senior Big Data Developer with 5+ years of experience in big data engineering, API integration, and AI-assisted development. The ideal candidate will design, build, and maintain scalable data pipelines and backend systems in a enterprise environment.

Key Responsibilities

Big Data & Spark

Design and develop Spark-Scala applications for large-scale data processing on Hadoop/CDP clusters

Build and optimize ETL/ELT pipelines using Spark DataFrames, Datasets and Spark SQL

Tune Spark jobs for performance (partitioning, caching, broadcast joins, shuffle optimization)

Migrate Spark 2 applications to Spark 3 on Cloudera CDP platforms

Work with Parquet, ORC, Avro file formats on HDFS

SQL & Data Engineering

Write complex HiveQL / Spark SQL queries including window functions, CTEs, subqueries and aggregations

Design and maintain Hive external/managed tables and partitioned datasets

Optimize slow-running queries and resolve correlated subquery issues

Work with HDFS encryption zones and data governance requirements

Unix / Shell Scripting

Develop and maintain bash shell scripts for job orchestration and automation

Handle error management, return codes, logging and alerting in shell scripts

Manage HDFS operations (hdfs dfs commands), file transfers, and data validation

Manage Kerberos authentication (kinit, keytab handling)

API Extraction & Integration

Build scripts and pipelines to extract data from REST APIs using curl and Python

Handle OAuth2 token generation, bearer token refresh and API health checks

Parse and process JSON API responses and load into HDFS/Hive

Manage pagination, error handling and retry logic for API calls

Work with enterprise API gateways and URL parameter construction

AI & Copilot Capabilities

Leverage GitHub Copilot / AI coding assistants to accelerate development

Use AI tools for code review, SQL generation, script debugging and documentation

Contribute to AI-assisted data quality and anomaly detection pipelines

Explore and implement LLM-based automation for repetitive data engineering tasks

Scheduling & Orchestration

Schedule and manage jobs using AAP (Ansible Automation Platform) / Control-M / cron

Build and maintain Ansible playbooks for automated deployments

Manage deployment pipelines including artifact versioning, Vault secret injection and environment-specific configuration

Monitor job health, handle failures and implement alerting

Nice to Have

• Experience with Cloudera CDP (7.x) and migration from HDP
• Knowledge of Kerberos, Vault, HDFS encryption zones
• Familiarity with CI/CD pipelines (Helios, GitHub Actions)
• Experience with MSSQL / JDBC connectivity from Spark
• Understanding of AML / Financial regulatory data domains.