Architect - Enterprise Application - SAP N 4D

Genpact · Hyderabad

Apply on the company website

Ready to turn bold ideas into real-world impact?
 At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory, our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI, our breakthrough solutions tackle companies’ most complex challenges.
 
If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. 
 
Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises.
 Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook.

Job Description

Job Purpose :

Data Platform Services is building a governed, metadata-driven data integration and staging platform centered on SAP BusinessObjects Data Services (BODS) and enterprise databases/data lakes — spanning source ingestion (SAP ERP/S/4HANA, non-SAP systems), a source-faithful central staging repository, long-term archival, and controlled distribution to multiple downstream systems. 

We're looking for a DataOps Engineer who treats ETL pipeline design, data flows, and access-control logic as configuration, not one-off code — someone who builds and maintains systems where metadata tables and control frameworks drive what gets executed (jobs, interfaces, delta loads, transformations, and security masking), rather than hand-crafting individual one-off BODS jobs for every new dataset or consumer. 

You'll work across ingestion (landing → central staging → archive), retention/partitioning strategy, and the routing/distribution rules engine that determines how data is extracted, transformed, filtered, or masked across multiple major downstream systems. 

What You'll Do 

• Build and operate robust batch and incremental change data capture (CDC) ingestion pipelines using SAP Data Services (BODS) from SAP (ECC, S/4HANA, SLT, ODP/Extractors) and non-SAP sources into central staging repositories/databases (e.g., SQL Server, Oracle, SAP HANA, or Cloud Storage). 

• Design and maintain metadata-driven ETL generation & execution frameworks — where dataset onboarding (new source table, delta logic, schema mapping, validation rules) is driven by configuration tables and reusable BODS templates/scripts rather than creating bespoke data flows from scratch. 

• Implement and maintain partition-based retention, database archiving, and extraction routines for historical data and rolling window retention policies (e.g., current + N prior years). 

• Build and maintain a dataset routing-rules engine: a governed metadata table (splittable, target_systems[], row_filter_expr, column_mask_expr) that programmatically directs and transforms BODS distribution jobs and target views per downstream system. 

• Own BODS repository architecture & governance: manage local/central repositories, Data Services Management Console (DSMC), user access security, environment promotion (Dev/Test/Prod), and execution auditing/lineage. 

• Drive DataOps & CI/CD automation: streamline BODS export/import/transport automation, repository synchronization, and job scheduling via Enterprise Scheduling tools (e.g., Autosys, Control-M, Airflow, or Azure Data Factory). 

• Monitor pipeline health, job execution logs, CDC checkpoint integrity, schema drift, and data SLAs; establish automated alerting and self-healing for job failures and data-freshness breaches. 

• Collaborate with upstream SAP functional/basis teams to define data contracts (e.g., Delta queue/ODP parameters, timestamps, extraction load impact) and downstream teams to translate their access/filter requirements into routing rules. 

• Document pipeline architecture, data dictionaries, retention policies, and routing logic for auditability and seamless developer onboarding. 

🛠️ Required Skills & Experience 

Core Platform & SAP BODS 

• Hands-on experience with SAP Data Services (BODS 4.x) designing complex Batch Jobs, Real-time Services, Workflows, Data Flows, and custom Scripts/Functions. 

• Strong expertise in extracting data from SAP environments (SAP S/4HANA, ECC, BW, ODP extractors, SLT, IDocs, RFC/BAPIs) as well as non-SAP flat files, REST APIs, and relational databases. 

• Deep proficiency in SQL and relational database internals (e.g., SAP HANA, SQL Server, Oracle): query optimization, indexing, table partitioning, push-down SQL execution, and incremental CDC logic. 

• Solid experience with BODS Central Repository management, object check-in/out workflows, version control, and multi-user development standards. 

Metadata-Driven Engineering (Critical) 

• Demonstrable background designing or maintaining metadata/config-driven ETL frameworks — e.g., control/registry tables driving dynamic SQL generation, parameterized BODS global variables, or generic reusable data flow templates. 

• Strong understanding of keeping generated ETL processes and target tables in sync with a source-of-truth ruleset, including schema versioning and change auditability. 

• Experience implementing automated audit logging, error handling, row-count reconciliations, and execution metrics captured directly via BODS scripts and database tables. 

Platform Engineering / DataOps 

• ETL Orchestration & Scheduling: Experience managing automated job schedules and dependency management via BODS Management Console, Azure Data Factory, Control-M, Airflow, or Autosys. 

• CI/CD & Version Control: Experience applying software engineering discipline to BODS (e.g., Git integration/documentation, automated repository migrations, deployment scripts). 

• Scripting & Automation: Strong scripting skills using Python, PowerShell, or Bash to automate file transfers, API interactions, and operational tasks around the BODS platform. 

• Monitoring & Observability: Hands-on experience setting up alerting, performance bottleneck troubleshooting (memory/buffer tuning in BODS), and data validation frameworks. 

Governance & Collaboration 

• Working knowledge of enterprise data governance: access control models, data lineage, retention/compliance-driven deletion, and data masking/obfuscation techniques for sensitive data (PII). 

• Experience serving multiple downstream consumers with varying analytical and operational requirements by delivering filtered and governed interfaces. 

• Clear written communication habits; ability to articulate complex ETL architectures and governance rules to both technical and non-technical stakeholders. 

 Nice to Have 

• Experience with SAP Information Steward (data quality profiling, rule building, metadata management). 

• Hands-on experience integrating SAP BODS with cloud data platforms (Azure Data Lake Storage Gen2, Snowflake, Databricks, or AWS S3). 

• Exposure to SAP Landscape Transformation (SLT) or SAP Data Intelligence / Datasphere. 

• Experience in large-scale multi-tenant enterprise environments supporting cross-functional business domains (Supply Chain, Finance, Commercial). 

 What Success Looks Like in the First 6 Months 

• Config-Driven Onboarding: Standard source table onboarding (source → landing/staging) is reduced to a configuration-driven process using reusable BODS templates, drastically reducing manual job creation. 

• Automated Retention & Purging: Automated partition/date-based archiving and retention mechanisms are operational across staging repositories. 

• Operational Routing Rules: A central metadata-driven routing table governs downstream extraction/distribution, dynamically applying required column masking and row filters. 

• Resilient DataOps: Automated alerting, execution telemetry, and standard environment promotion workflows are established and fully documented. 

Qualifications

Certifications

Required Skills

Language

Language Proficiency -

Additional Job Location -

Job Type

Master Skill List -

Remote Type -

Work Shift -

Why join Genpact?

• Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter
• Make an impact – Help global enterprises solve business challenges that matter
• Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead
• Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day
• Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress

Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up.
Let’s build tomorrow together.
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

More jobs at Genpact · Other jobs in Hafeezpet Phoenix