Data Engineer

Weekday AI (YC W21); Mumbai; On-site; INR 500,000 - 2,000,000; Full time

Job summary

Weekday AI (YC W21) is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines using Azure Databricks, ADF, and SSIS. The role focuses on cloud-based ETL/ELT, data governance, and performance optimization to support BI and analytics initiatives.

The ideal candidate will have 5+ years in data engineering, strong SQL and Spark skills, and a track record of delivering enterprise-grade data solutions in Azure and hybrid environments.

Qualifications

• 5-8 years of Data Engineering or ETL experience.
• Hands-on with Azure Databricks and ADF for data pipeline design.
• SSIS proficiency for on-prem and hybrid data integration.
• Strong SQL development and query optimization skills.
• Experience building scalable ETL/ELT pipelines and data warehousing concepts.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines ingesting data from multiple sources.
• Build scalable data processing using Azure Databricks and Spark.
• Develop and manage workflows with Azure Data Factory for orchestration.
• Create SSIS packages for on-prem and hybrid integration.
• Develop optimized SQL queries, stored procedures, and views for reporting.
• Collaborate with business teams to translate data requirements into solutions.
• Ensure data quality through validation, cleansing, reconciliation, and monitoring.
• Optimize pipeline performance, troubleshoot bottlenecks, and ensure reliability.
• Integrate structured and semi-structured data from enterprise systems.
• Monitor production pipelines and implement proactive monitoring.

Skills

Azure Databricks

ADF

SSIS

SQL

ETL

Spark

Data Lake Storage

PySpark

SQL Performance

Data Modeling

Git

Delta Lake

Spark SQL

Education

Bachelor's degree in CS/IT/Engineering

Tools

Git

Azure DevOps

Job description

This role is for one of the Weekday's clients

Salary range: Rs 500000 - Rs 2000000 (ie INR 5 - 20 LPA)

Min Experience: 5+ years

Location: Mumbai, Maharashtra, India

JobType: full-time

We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and enterprise-grade data integration solutions. The ideal candidate will have strong expertise in Microsoft Azure data services, particularly Azure Databricks, Azure Data Factory (ADF), and SQL Server Integration Services (SSIS). You will work closely with data architects, analysts, and business stakeholders to build reliable data platforms that support reporting, analytics, and business intelligence initiatives.

This role requires hands‑on experience in data transformation, ETL/ELT development, cloud‑based data engineering, and performance optimization. The ideal candidate should be passionate about building high‑quality, scalable, and efficient data solutions while ensuring data accuracy, security, and governance.

Requirements

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading data from multiple sources
• Build and optimize scalable data processing solutions using Azure Databricks and Apache Spark
• Develop and manage workflows using Azure Data Factory for orchestrating enterprise data movement and transformation
• Create, maintain, and enhance SQL Server Integration Services (SSIS) packages for on‑premises and hybrid data integration requirements
• Develop optimized SQL queries, stored procedures, views, and database objects to support reporting and analytics
• Collaborate with business teams to understand data requirements and translate them into technical solutions
• Ensure data quality through validation, cleansing, reconciliation, and monitoring processes
• Optimize pipeline performance, troubleshoot bottlenecks, and implement best practices for scalability and reliability
• Integrate structured and semi‑structured data from multiple enterprise systems
• Monitor production data pipelines, resolve failures, and implement proactive monitoring mechanisms
• Participate in code reviews, documentation, and knowledge‑sharing initiatives
• Follow data governance, security, compliance, and best practices throughout the data lifecycle
• Support migration of legacy ETL processes to modern Azure‑based data platforms where applicable

Must‑Have Skills

• 5-8 years of experience in Data Engineering or ETL Development
• Strong hands‑on expertise in Azure Databricks
• Extensive experience with Azure Data Factory (ADF)
• Proficiency in SQL Server Integration Services (SSIS)
• Strong SQL programming skills with experience in query optimization and performance tuning
• Experience developing scalable ETL/ELT pipelines
• Good understanding of Azure Data Lake Storage and cloud‑based data architectures
• Experience with Apache Spark using PySpark or Spark SQL
• Strong knowledge of relational databases and data warehouse concepts
• Familiarity with data modeling, data transformation, and data integration techniques
• Experience with source control systems such as Git
• Strong analytical, troubleshooting, and problem‑solving skills

Good‑to‑Have Skills

• Experience with Azure Synapse Analytics
• Knowledge of Azure SQL Database or SQL Server administration
• Familiarity with Delta Lake architecture
• Experience with CI/CD pipelines for Azure data solutions
• Exposure to Power BI or other business intelligence tools
• Understanding of DevOps practices for data engineering
• Experience working with REST APIs and data ingestion from external systems
• Knowledge of data governance, security, and compliance standards
• Familiarity with Agile/Scrum development methodologies

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field
• Microsoft Azure Data Engineer certification is an added advantage
• Excellent communication and stakeholder management skills
• Ability to work independently while collaborating effectively within cross‑functional teams
• Strong commitment to delivering high‑quality, scalable, and maintainable data engineering solutions