Role OverviewWe 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.
The base compensation range for this role in the posted location is: 79,000 to 102,000.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
