Job Description

Role: Sr. Data Engineer
Experience: 3-8Years
Employment Type: Full-Time
Location: Hyderabad / Ahmedabad / Indore
Work Mode: To Be Confirmed
Department: Data Engineering / Analytics
Reporting To: Data Engineering Lead / Data Architect

About the Role

We are looking for an experienced Senior Data Engineer with 3 to 8 years of experience in designing, developing, and optimizing scalable data pipelines and analytics solutions.

The candidate should have strong hands-on experience in at least one of the following platforms: Databricks, Microsoft Fabric, or Snowflake, along with Power BI expertise. The role involves building reliable ETL/ELT pipelines, implementing data lakehouse and warehouse architectures, optimizing data workflows, and developing dashboards to support business decision-making.

The candidate will collaborate with cross-functional teams to ensure data quality, governance, security, performance, and scalability across cloud-based data platforms.

Roles and Responsibilities

Data Engineering & Pipeline Development

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, Microsoft Fabric, or Snowflake.

• Build and optimize data ingestion, transformation, and integration workflows.

• Develop reusable and automated data processing solutions.

• Troubleshoot pipeline failures and ensure reliable data delivery.

• Optimize data processing performance, scalability, and cost efficiency.

Data Architecture & Cloud Platforms

• Implement and maintain data lakes, data warehouses, and lakehouse architectures.

• Work with cloud platforms such as Azure, AWS, or GCP.

• Design efficient data models to support analytics and reporting requirements.

• Work with technologies such as Delta Lake, Azure Synapse, or Snowflake optimization features.

• Ensure data architecture follows scalability, performance, security, and governance standards.

Power BI & Data Visualization

• Develop, maintain, and optimize Power BI dashboards and reports.

• Create data models, relationships, measures, and calculations using DAX.

• Optimize dashboard performance and improve report usability.

• Translate business requirements into meaningful reports and visualizations.

• Collaborate with business stakeholders to deliver actionable insights.

Data Quality, Governance & Security

• Implement data quality checks and validation mechanisms.

• Ensure data accuracy, integrity, consistency, and reliability.

• Follow data governance, lineage, security, and compliance standards.

• Monitor data pipelines and resolve data discrepancies.

• Maintain appropriate access controls and data protection practices.

Automation, CI/CD & Performance Optimization

• Automate data workflows and recurring data processing activities.

• Implement CI/CD practices for data engineering solutions.

• Use Git and version control for code management.

• Monitor pipeline performance, troubleshoot failures, and improve reliability.

• Identify opportunities to improve system efficiency and reduce operational costs.

Collaboration & Stakeholder Management

• Collaborate with data analysts, BI developers, architects, and business stakeholders.

• Understand business requirements and translate them into technical solutions.

• Participate in technical discussions, design reviews, and solution planning.

• Document data pipelines, architecture, processes, and technical standards.

• Support advanced analytics and machine learning initiatives where required.

Required Skills & Experience

• 5–7 years of relevant experience in Data Engineering.

• Strong hands-on experience in at least one of the following: Databricks, Microsoft Fabric, or Snowflake.

• Hands-on experience with Power BI, including data modeling, DAX, dashboard development, and performance optimization.

• Strong proficiency in SQL and experience with at least one programming language: Python, Scala, or Java.

• Experience designing, developing, and maintaining scalable ETL/ELT pipelines.

• Experience with data modeling and data integration in cloud environments.

• Working knowledge of Azure, AWS, or GCP data services.

• Understanding of data lakes, data warehouses, and lakehouse architectures.

• Experience with data quality, validation, monitoring, and troubleshooting.

• Knowledge of version control and CI/CD practices.

• Strong analytical, problem-solving, and communication skills.

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Primary Skills (Must Have)

• Databricks / Microsoft Fabric / Snowflake — at least one mandatory

• Power BI

• SQL

• Python / Scala / Java

• ETL/ELT Pipeline Development

• Data Modeling

• Cloud Data Engineering

• Data Lake / Data Warehouse / Lakehouse

• DAX & Power BI Dashboard Development

• Data Quality & Pipeline Monitoring

• Performance Optimization

Secondary / Good to Have Skills

• Apache Kafka

• Azure Event Hubs / AWS Kinesis

• Delta Lake

• Azure Synapse Analytics

• Snowflake Performance Optimization

• CI/CD for Data Engineering

• Git & Version Control

• Infrastructure as Code

• Machine Learning Pipelines

• Advanced Analytics

• Data Governance & Lineage

• Compliance Frameworks

Key KPIs

• Reliability and availability of data pipelines

• On-time delivery of data engineering solutions

• Pipeline performance and processing efficiency

• Data quality, accuracy, and consistency

• Power BI dashboard performance and usability

• Reduction in pipeline failures and processing delays

• Cloud resource utilization and cost optimization

• Compliance with data security and governance standards

• Automation and deployment efficiency

• Stakeholder satisfaction and business reporting effectiveness

Candidate Profile

• Strong technical expertise in at least one core data platform: Databricks, Microsoft Fabric, or Snowflake.

• Hands-on experience building production-grade data pipelines and analytics solutions.

• Good understanding of both data engineering and business intelligence requirements.

• Ability to troubleshoot complex data issues and optimize performance.

• Quality-focused, analytical, and proactive in identifying improvements.

• Comfortable collaborating with technical teams and business stakeholders.

• Able to take ownership of data solutions from development through deployment and maintenance.

Interview Details

Round 1: Internal Screening – Experience, Core Skills & Project Assessment

Round 2: Technical Interview – Data Engineering, Cloud Platforms, SQL, and Power BI

Interview Mode: Virtual And F2F

Requirements

Benefits