Key Responsibilities

Data Platform & Architecture

- Design and implement scalable data architectures including data lakes and data warehouses using Azure ecosystem (e.g., Microsoft Fabric, ADLS).
- Define data models and storage strategies for structured and unstructured data.

Data Pipeline Development

- Build and manage end-to-end data pipelines (ETL/ELT) to ingest, transform, and serve large-scale datasets.
- Ensure reliability, performance, and scalability of data pipelines.

Analytics Enablement

- Develop and standardize analytics frameworks and reusable data models to support reporting, BI, and advanced analytics.
- Enable self-service analytics through curated datasets and semantic layers.
- AI/ML, Analytics & Storytelling: Working knowledge of machine learning techniques and analytics use cases, with the ability to operationalize models within data platforms. Strong capability in data storytelling , translating complex data into intuitive visualizations and actionable insights for business stakeholders.

Hands-on Technical Leadership

- Remain hands-on with tools such as Python, SQL, and MS Fabric for data processing and transformation.
- Guide the team on best practices in data engineering, modeling, and performance optimization.

Team & Delivery Management

- Lead and mentor a team of data engineers / analysts / data scientists.




- Drive project delivery across multiple initiatives, ensuring timelines and quality.

Stakeholder Collaboration

- Work closely with business, analytics, and engineering teams to translate requirements into scalable data solutions.
- Support downstream use cases including BI, reporting, and machine learning.

Data Governance & Quality

- Establish data governance standards, including data quality, lineage, access control, and cataloging .
- Ensure compliance with enterprise data policies.

Qualifications

- Experience: 8-12 years in data engineering / data science / analytics, with 2-4 years in a managerial role.
- Education: Bachelor's/ master's in computer science, Data Engineering, Data Science, or related field.

Technical Skills

- Core:
- Advanced SQL (must-have)
- Strong Python for data processing (pandas, PySpark preferred)

- Data Platforms:

- Hands-on experience with Microsoft Fabric , Azure Data Lake, Azure Synapse, Data Factory

- Data Engineering:

- Strong expertise in ETL/ELT pipeline design , orchestration, and optimization
- Experience working with large-scale datasets (batch and near real-time)

- Data Modeling:

- Solid understanding of data warehouse concepts (star/snowflake schema, dimensional modeling)

- BI & Analytics:

- Working knowledge of Power BI / Tableau and semantic modeling .

📌 Data Scientist III (Bengaluru)
🏢 Conduent
📍 Bengaluru