Abinitio Developer

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.