Ab Initio Developer
Indexed description
Work You'll Do/Responsibilities
As an Ab Initio ETL Developer, you will design, build, and optimize high-volume data integration pipelines for financial services clients. In this client-facing technical role, you will leverage your deep expertise in the Ab Initio platform and Oracle databases to process massive enterprise datasets securely and efficiently. You will bridge the gap between business needs and technical execution by collaborating tightly with data architects and business analysts. By translating complex requirements into scalable technical solutions, you will ensure seamless source-to-target data integration while maintaining the agility to navigate shifting deadlines and unexpected changes within a fast-paced, highly regulated environment.
- High-Volume ETL Development: Design, develop, test, and deploy complex, high-volume Extract, Transform, Load (ETL) solutions for clients using the Ab Initio platform, with a specific focus on FDC Gateway integrations.
- Data Analysis & Integration: Perform rigorous data analysis, complex data mapping, and precise source-to-target integration to ensure seamless data flow across heterogeneous enterprise systems.
- Oracle Database & Pipeline Optimization: Write, optimize, and troubleshoot advanced Structured Query Language (SQL) and Procedural Language/Structured Query Language (PL/SQL) queries. Implement the required optimizations for high-volume data handling to ensure maximum throughput and resolve latency bottlenecks.
- Requirements Translation: Collaborate directly with business analysts, data architects, and other cross-functional stakeholders to translate ambiguous business requirements into robust, scalable technical solutions.
- Agile Adaptability & Delivery: Work effectively under pressure to manage strict project deadlines, adapting swiftly to unexpected changes in client expectations, requirements, or technical constraints.
- Technical Documentation & Quality Assurance: Create and maintain clear technical documentation, data lineage mapping, and standard operating procedures to ensure sustainable delivery and seamless knowledge transfer.
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required
- 4+ years of data engineering and ETL development experience within the Financial Services industry.
- 4+ years of hands-on experience developing complex, high-volume ETL pipelines directly on the Ab Initio platform, including demonstrable proficiency working with the FDC Gateway.
- Experience in Oracle databases, including advanced SQL, PL/SQL programming, execution plan analysis, and database performance tuning.
- Understanding of enterprise data warehousing methodologies (e.g., Kimball, Inmon) and dimensional modeling techniques (Star and Snowflake schemas) to build and populate efficient data structures.
- Experience designing robust error-handling, data reconciliation, and reject-processing frameworks to ensure pristine data quality and prevent data loss within financial pipelines.
- Hands-on experience integrating ETL deployments into modern Continuous Integration/Continuous Deployment (CI/CD) pipelines utilizing version control and automation tools such as Git, Jenkins, or Azure DevOps.
- High-Volume Data Handling: Demonstrated expertise in applying necessary optimizations for high-volume data processing, ensuring robust performance and stability across enterprise pipelines.
- Finance & Banking Data Domain: Familiarity with finance and banking data domains, including hands-on experience in the complex transformation, mapping, and rigorous validation of financial datasets.
- Communication Skills: Consistently demonstrates clear and concise written and verbal communication skills, with the ability to articulate complex technical concepts to both engineering teams and business stakeholders.
- Resilience & Problem Solving: Exceptional ability to work under pressure, manage competing deadlines, and maintain delivery excellence amidst shifting project priorities.
- Big Data & Enterprise Data Warehousing: Proven experience working directly with, rigorously reconciling, and actively managing a large-scale Enterprise Data Warehouse (EDW) designed to support complex big data analytics and reporting initiatives.
- Modern Data Platforms & Streaming: Understanding of or working experience with distributed SQL query engines (such as Trino or Starburst) and experience integrating with real-time data pipelines utilizing Apache Kafka.
- Job Scheduling & Orchestration: Hands-on experience with modern data orchestration tools such as Apache Airflow, as well as traditional enterprise job schedulers (e.g., Control-M, AutoSys) and Unix/Linux shell scripting.
- Application Integration: Familiarity with or exposure to Java and Spring Boot based applications, particularly regarding Application Programming Interface (API) integrations and data payload handling.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
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