Lead Data Engineer

WhiteBlue Inc.; Chennai; Ibrido; INR 3.000.000 - 5.500.000; Tempo pieno

Descrizione del lavoro

WhiteBlue Inc. is seeking a senior data engineer to build scalable data pipelines using Python, SQL and cloud data platforms. You will work in a hybrid/remote setup with 8+ years of experience, focusing on AI-enabled analytics, data ingestion, transformation and governance across Snowflake, ADF and Microsoft Fabric ecosystems.

The role emphasizes advanced SQL, data visualization with Power BI/Tableau, and collaboration within cross-functional teams to deliver enterprise analytics solutions.

Competenze

• 8+ years of experience in data engineering/analytics engineering roles.
• Experience with building scalable data pipelines ingesting diverse data sources.

Conoscenze

Python

SQL

AI/ML development

API integration

Data transformation

Data analytics

Agile/Scrum

Strumenti

Snowflake

Azure Data Factory

Microsoft Fabric

Power BI

Tableau

SQL Server

GitHub/GitLab

Azure DevOps

Jira

Confluence

SharePoint

Descrizione del lavoro

Build scalable data pipelines using Python, SQL, Snowflake, Azure Data Factory and Microsoft Fabric, with expertise in AI and analytics.

Employment Type:

Full Time

Timing:

3:00 AM to 12 Noon PST

Work Mode:

Hybrid/Remote

Experience:

8+ years

Location:

Required Skills:

Experience in Data Engineering, Analytics Engineering, Data Platforms, or related data & AI roles.

Strong proficiency in Python for data engineering, automation, API integration, data transformation, and AI/ML solution development.

Hands-on experience with modern Cloud Data Platforms such as Snowflake, Azure Data Factory (ADF), Microsoft Fabric, Advanced Analytics, Tableau or equivalent technologies.

Expertise in designing and building scalable data pipelines to ingest, process, and manage structured, semi-structured, and unstructured data from files, APIs, databases, and cloud sources.

Advanced SQL skills and experience working with relational databases such as SQL Server and cloudnative data warehouses.

Experience leveraging Generative AI, Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), Vector Databases, and AI-powered analytics solutions in enterprise environments.

Proficiency in data visualization and analytics tools such as Power BI, Tableau, Python visualization libraries, and self-service analytics platforms.

Experience implementing data quality frameworks, data observability, metadata management, data governance standards, and technical data catalogs/dictionaries.

Familiarity with Machine Learning lifecycle concepts (MLOps) including model deployment, monitoring, prompt engineering, and responsible AI practices.

Experience with DevOps, CI/CD, Infrastructure as Code (IaC), Git-based development workflows, and Agile/Scrum methodologies.

Proficiency with collaboration and project management tools including Jira, Confluence, SharePoint, GitHub/GitLab, and Azure DevOps.

Strong analytical thinking and innovative problem-solving skills with the ability to leverage AI-assisted development tools to accelerate delivery and improve productivity.

Proven ability to rapidly learn and adopt emerging technologies in the evolving Data, Analytics, and AI landscape.

Demonstrates a Team-First mindset, fostering collaboration and contributing to the maturity of enterprise Data, Analytics, and AI platforms.

Experience in Financial Services, Banking, Credit Union, FinTech, or related regulated industries is preferred.

Knowledge of data security, privacy, compliance, and Responsible AI governance within regulated environments is highly desirable.