Data Engineer - BODS
At a glance
Mid-level Data Engineering role at Weekday AI. Pune · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune data flows that integrate and transform information for the enterprise warehouse
- Create ETL/ELT pipelines with SAP BODS and IBM DataStage, then improve job speed and reliability
- Shape warehouse models using star or snowflake designs and SCD patterns; manage incremental loads and reconciliation
- Write and tune Oracle SQL, procedures and functions, including indexing and database performance work
- Guide data engineers through reviews and standards, while working with stakeholders to turn needs into technical solutions
What you bring
- At least eight years in data engineering and two years leading technical teams
- Strong SAP BODS, SQL and IICS skills, with practical IBM DataStage experience
- Deep knowledge of Oracle and enterprise warehouse architecture, including data modeling and ETL practices
- A bachelor’s or master’s degree in computer science, information systems or a related area
Who this fits
This role suits a senior, hands-on data engineer who can lead and mentor a team while collaborating with business and technical stakeholders. You must be flexible to work shifts. The listing gives Pune and Bengaluru as locations.
From the employer
This role is for one of the Weekday's clients
Min Experience: 5+ years
Location: Pune, Bengaluru
JobType: full-time
We are seeking an experienced Lead Data Engineer to take end-to-end ownership of Enterprise Data Warehouse (EDW) solutions. This role will be responsible for designing, architecting, and optimizing scalable, secure, and high-performance data pipelines using SAP BODS, IBM DataStage, Redwood, SQL, Oracle, and modern data platforms.
The ideal candidate will combine strong hands-on technical expertise with leadership capabilities to drive data engineering best practices and deliver enterprise-grade data solutions aligned with business objectives.
Requirements
Key Responsibilities
1. EDW Architecture & Data Engineering
- Design and implement scalable data integration and transformation frameworks for the Enterprise Data Warehouse.
- Architect and optimize ETL/ELT pipelines using SAP BODS and IBM DataStage.
- Develop and maintain robust data models (Star/Snowflake schemas, SCD implementation).
- Ensure high availability, reliability, and performance of data pipelines.
- Implement data governance, security, and compliance standards.
2. ETL Development & Optimization
- Develop complex data workflows and transformations.
- Perform performance tuning of ETL jobs and SQL queries.
- Optimize batch processing and scheduling using Redwood.
- Implement error handling, logging, and monitoring mechanisms.
- Manage incremental loads and data reconciliation processes.
3. Database & SQL Development
- Write and optimize complex SQL queries, stored procedures, and functions.
- Work extensively with Oracle databases and related technologies.
- Design and manage indexing strategies and query optimization.
- Support database performance analysis and tuning.
4. Leadership & Team Management
- Lead and mentor a team of data engineers.
- Conduct code reviews and enforce development standards.
- Drive technical best practices and architecture governance.
- Collaborate with cross-functional teams including BI, Analytics, and Application teams.
- Participate in sprint planning, estimation, and technical roadmap discussions.
5. Stakeholder Collaboration
- Work closely with business stakeholders to gather and translate requirements into technical solutions.
- Provide technical guidance and solution recommendations.
- Ensure alignment between enterprise data strategy and business goals.
- Support production issue resolution and root cause analysis.
Required Skills
Technical Expertise
- Strong experience with SAP BODS
- Hands-on experience with IBM DataStage
- Experience with Redwood scheduling
- Advanced SQL development
- Strong expertise in Oracle database
- Deep understanding of Enterprise Data Warehouse architecture
Data Engineering Concepts
- Data modeling (Star/Snowflake schema, SCD Types)
- ETL/ELT best practices
- Data quality frameworks
- Performance tuning and optimization
- Data security and governance standards
Preferred / Good to Have
- Experience with modern cloud data platforms (Azure, AWS, GCP)
- Knowledge of Snowflake, Databricks, or Synapse
- CI/CD implementation for data pipelines
- Exposure to data cataloging and metadata management tools
- Experience in Agile/Scrum methodologies
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
- 8+ years of experience in Data Engineering.
- 2+ years of experience in leading technical teams.
Key Competencies
- Strong architectural and analytical skills
- Leadership and mentoring capability
- Excellent communication and stakeholder management
- Problem-solving mindset
- Ability to drive enterprise-scale data initiatives
- Flexibility for Shift working is mandatory.
Must-have skills
SAP BODS, SQL, IICS
Good-to-have skills
redwood, Python, Banking Domain
Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Engineering
Find me workBy the team behind dataroles.