Role OverviewAs the Technical Lead - Data Engineering, you will architect, lead, and drive the technical execution of a high-throughput, near real-time data caching layer supporting Operational Data Store (ODS) views. You will lead the engineering team responsible for ingesting high-frequency account update events (via Kafka/CDC), orchestrating cache refreshes, and designing high-performance PostgreSQL persistence architectures on AWS to guarantee sub-second lookups and rock-solid consistency for downstream consumers. 8+ years in Data Engineering with at least 2+ years in a lead or principal role.
Key Responsibilities • Architecture & Technical Leadership: Define the end-to-end data architecture, data modeling, partitioning, indexing, and retention strategies for high-volume PostgreSQL/Aurora workloads.
• Team Guidance & Code Quality: Lead and mentor a team of Senior and Mid-level Data Engineers; establish best practices for SQL performance tuning, database migrations (Liquibase), and CI/CD pipelines.
• Caching: Build cache read/write logic in Amazon Elastic Cache (Redis), including key design, TTLs and invalidation handling.
• Performance Tuning: Monitor and improve high-throughput read/write queries, lock contention and index overhead.
• Real-Time & Batch Pipelines: Architect event-driven ingestion pipelines to consume events from event streams, driving near real-time cache invalidation and refresh mechanisms.
• Data Integrity & Reconciliation: Design automated reconciliation frameworks and audit jobs to detect cache drift against source ODS views and guarantee consistency.
• AI-Assisted Engineering: Drive adoption of AI-assisted engineering tools (code generation, SQL optimization, test automation) to accelerate delivery and ensure robust test coverage.
• Cross-Functional Collaboration: Partner closely with Service Modernization leads, API engineers, enterprise architects, and platform/cloud operations.
Required Qualifications & Experience • AWS Data Ecosystem: Amazon Aurora PostgreSQL, RDS, and DynamoDB
• Experience in Data Modeling (ODS, transactional cache patterns), Partitioning, Indexing strategies, and Data Retention/Archival policies
• Caching: Hands-on experience with Amazon Elastic Cache (Redis), including cache design, key and TTL strategies, invalidation patterns and keeping cache data consistent with the source
• Programming: Proficient in Java/Python
• Streaming & Messaging: Apache Kafka or AWS MSK event consumption and offset management.
• Hands-on experience integrating AI-assisted development & testing practices into engineering workflows
• Expert-level PostgreSQL / Advanced SQL: (query optimization, execution plan analysis, vacuuming, connection pooling).
• Database DevOps: Schema version control using Liquibase or Flyway.
• Proven track record with large-scale ETL/ELT pipelines and Change Data Capture (CDC) / stream-based data synchronization.
• Financial services, core banking, or payment platforms experience: (ODS familiarity is a strong plus).
The base compensation range for this role in the posted location is: 89,000 to 120,000.
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.
