Job Description :

1. Profile :

Designation : Lead Data and Analytics Engineer

Location : Head Office, New Delhi

Reports to Head : DCoE

Qualification : B.Tech/MCA

Experience : 10 to 12 Years

2. Major Responsibilities :

Position Overview :

We are seeking a hands-on Senior Data & Analytics professional who will design, build, and operate the enterprise data and analytics ecosystem covering :

- Data Engineering & Data Platforms (lake/lakehouse/warehouse)

- Business Intelligence (BI) & Analytics delivery

- AI-ready data preparation and modeling

- Embedded and platform-native AI capabilities within analytics tools

This role is focused on doing rather than managing the individual will personally perform data ingestion, transformation, modeling, semantic layer creation, BI dashboard development, and AI-enabling data preparation using platforms such as Microsoft Fabric, Snowflake, Databricks, and Power BI / Qlik Sense / Tableau.

Key Responsibilities :

1. Hands-on Data Platform & Architecture:

- Design and implement modern data architectures (lakehouse, warehouse, data fabric patterns).

- Configure and develop data solutions on :

a. Microsoft Fabric (preferred) and/or

b. Snowflake / Databricks

- Define data domain models, curated layers, and gold datasets suitable for BI and AI workloads.

- Optimize performance, scalability, and cost across compute and storage layers.

2. Data Engineering & ETL/ELT (Hands-on):

- Personally build and maintain batch and near-real-time data pipelines.

- Use SQL, Spark, and platform-native tooling for :

a. Data ingestion from SAP, MES, SCADA, historians, sales, dealer and operational systems.

b. Data cleansing, enrichment, transformation, and harmonization.

- Implement data quality checks, error handling, lineage, and documentation.

- Structure data using AI-ready patterns (feature-friendly schemas, clean dimensions, reusable facts).

3. AI Readiness & AI-Enabled Analytics:

- Prepare and curate high-quality, trusted, AI-ready datasets for :

a. Machine learning

b. Advanced analytics

c. Copilot / GenAI-based analytics experiences

- Implement data preparation best practices for AI, including :

a. Feature-ready modeling

b. Metadata enrichment

c. Versioning and reproducibility

- Leverage built-in / native AI features available in platforms such as :

a. Microsoft Fabric (Copilot, AI-assisted pipelines, notebooks)

b. Power BI (AI visuals, Copilot, smart narratives, Q&A)

- Work closely with business and IT to ensure data suitability for future AI use cases.

4. BI & Analytics Development (Hands-on):

- Design and develop enterprise BI solutions using :

a. Power BI (strongly preferred)

b. Qlik Sense and/or Tableau

- Build semantic models, measures, KPIs, and calculations personally.

- Create dashboards for manufacturing, Sales and corporate functions :

a. Sales, product pricing, market share analytics

b. OEE, downtime, yield, quality

c. Production efficiency, energy usage

d. Supply chain, inventory, procurement

- Ensure performance optimization, usability, and data security in BI assets.

- Enable guided self-service analytics through certified datasets and reusable models.

5. Manufacturing Analytics Enablement

- Work hands-on with manufacturing data sources :

a. SAP ECC/S/4HANA

b. MES, SCADA, historians (OSI PI or similar)

c. Quality, maintenance, and production systems

- Translate plant and business requirements into data models and dashboards.

- Support operational analytics use cases that drive measurable outcomes.

6. Governance, Security & Best Practices

- Implement role-based security, row-level security, and controlled data access.

- Apply data governance practices (cataloguing, naming standards, documentation).

- Ensure compliance with internal IT, security, and data policies.

Required Skills & Competencies :

Technical (Must-Have):

- Hands-on experience with :

a. Microsoft Fabric / Snowflake / Databricks

b. SQL and Spark-based data processing

- Strong data modeling skills (dimensional/star schemas).

- BI development experience with Microsoft Power BI.

- Strong understanding of AI-ready data preparation concepts.

- End-to-end ownership of data pipelines and BI artifacts.

- Manufacturing & Sales Domain (Highly Preferred)

- Experience working with manufacturing or process industry data.

- Experience working with sales and marketing, DMS data.

- System integration understanding across ERP and plant systems.

Soft Skills :

- Ability to work independently and own deliverables end-to-end.

- Strong problem-solving and analytical mindset.

- Comfort working directly with business users and plant stakeholders.