Role Overview:
A Data Engineering / Data Architect role centered on understanding business requirements, translating them into technical data solutions, and managing end-to-end data workflows. The role involves strong collaboration with business stakeholders and technical teams, with a focus on ETL design and development using Ab Initio and related technologies.
Key Responsibilities:
- Business & Data Requirement Translation:
- Understand business needs and translate into data mapping and technical requirements.
- Work closely with product owners, business analysts (BAs), and tech teams for complete data understanding.
- Data Modeling & ETL Development:
- Design and create data models for data marts.
- Design ETL mappings and support ETL development teams.
- Interface and support ETL and technology teams for technical and functional clarity.
- Data Quality & Validation:
- Perform data profiling on new source systems.
- Conduct data reconciliation between source and target systems.
- Advanced Data Analytics:
- Perform exploratory data analysis and feature engineering for ML use-cases.
- Generate actionable insights independently and present to management/stakeholders.
- Strategy & Collaboration:
- Support development of data-driven strategies (e.g., sales, cost reduction).
- Lead partnerships with external parties for knowledge sharing and joint projects.
- Define and guide the strategic technical direction for data.
- Project & Stakeholder Management:
- Manage relationships and task assignments with program stakeholders and partner teams.
- Track deliverables and provide timely, accurate delivery status reports.
- Drive continuous improvement on team delivery effectiveness.
Required Skills & Experience:
- Technical Expertise:
- Strong experience with Ab Initio (CoOp, ConductIt, AI Enterprise Meta Environment).
- Solid experience with relational databases (Oracle, SQL Server, PL/SQL).
- Expertise in ETL technologies including Hadoop.
- Proficient with UNIX scripting, DB, and TWS scheduling.
- Strong understanding of data warehousing and data lakes.
- Methodologies & Processes:
- Experience with Agile methodologies and SDLC.
- Requirement gathering, analysis, and software design.
- Soft Skills:
- Strong data analysis and communication skills.
- Ability to present technical findings clearly to business users.
- Quick learner with excellent analytical and multitasking skills.
- Ability to build strong relationships across business and tech teams.
