Python Fullstack with Microservices: Software Development Lead
Job requirements
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.
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
Bachelors or Masters degree in Computer Science Information Systems or related field.
5 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
Please Note
This is L3 support project
Flexibility to work in rotational shift is mandatory
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Senior IC
Senior Data EngineerPrimary SkillsCI/CD Pipeline CSS/SCSS/LESS PyTest PostgreSQL / MongoDB / Redis REST API / GraphQLSpecializationPython Fullstack with Microservices: Software Development LeadJob requirementsWe are seeking an experienced Lead Data Engineer to take end-to-end ownership of Enterprise...
Python Fullstack with Microservices: Software Development Lead
Job requirements
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.
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
Bachelors or Masters degree in Computer Science Information Systems or related field.
5 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
Please Note
This is L3 support project
Flexibility to work in rotational shift is mandatory
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
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