Senior Data Engineer

Autodesk India Pvt Ltd.; Bengaluru; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

Autodesk India Pvt Ltd. in Bengaluru is seeking a Senior Data Engineer with 7+ years of hands-on experience to design, build, and optimize scalable data platforms and pipelines enabling analytics, ML, and BI across the organization.

You will architect data solutions, lead engineering efforts, mentor junior engineers, and collaborate with Data Science, Platform Engineering, Analytics, Product, and business stakeholders to deliver trusted, well-modeled datasets and governance-driven data

Qualifications

• Bachelor's degree in computer science, Information Technology, Engineering, or a related field (or equivalent practical experience)
• 7+ years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Data Systems
• Strong hands‑on expertise in: Python Spark / PySpark Advanced SQL Shell scripting
• Strong understanding of relational databases such as PostgreSQL and MySQL
• Experience working with NoSQL databases including MongoDB, Cassandra, DynamoDB, or equivalent
• Solid understanding of data modeling, data architecture, and warehouse design principles
• Experience designing and operating scalable ETL/ELT pipelines across batch and streaming environments
• Hands‑on experience with modern data technologies such as: Apache Kafka Apache Flink Apache Iceberg Hive Parquet
• Experience using workflow orchestration platforms such as Apache Airflow
• Strong experience with cloud platforms, preferably AWS, including: EMR Glue S3 IAM Lambda Step Functions Athena Redshift
• Experience with modern data warehouse platforms such as Snowflake, Amazon Redshift, or Google BigQuery
• Experience implementing CI/CD pipelines, version control using Git, and infrastructure automation
• Experience implementing data validation, monitoring, incremental processing, backfills, reconciliation, and operational support for production pipelines
• Proven ability to lead technical initiatives, influence architecture decisions, establish engineering standards, and mentor engineering teams

Responsibilities

• Design, develop, and maintain scalable, resilient, and high-performance data pipelines supporting batch and real-time workloads
• Build and optimize ETL/ELT pipelines for ingesting, transforming, validating, and serving large-scale datasets
• Design and implement robust data models, schemas, and storage strategies to ensure data quality, integrity, and accessibility
• Develop and optimize distributed data processing solutions using Spark, PySpark, SQL, and cloud-native technologies
• Integrate data from multiple enterprise systems while maintaining consistency, governance, and reliability
• Build and manage scalable data platforms using modern cloud services and data lake technologies
• Optimize database, warehouse, and pipeline performance for large-scale analytical workloads
• Implement monitoring, alerting, automated testing, and data quality validation across pipelines
• Establish and enforce data governance, security, compliance, and engineering best practices
• Partner with Product, Analytics, Data Science, Machine Learning, and Engineering teams to translate business requirements into scalable data solutions
• Enable self-service analytics by delivering trusted, well-modeled datasets
• Contribute to the technical roadmap by driving architecture discussions, defining engineering standards, and promoting reusable data platform components
• Mentor junior engineers through code reviews, technical guidance, and best practice adoption
• Maintain comprehensive technical documentation covering architecture, data models, workflows, and operational processes

Skills

Python

Spark / PySpark

SQL

Shell scripting

Data modeling

Data architecture

Leadership

Mentoring

Stakeholder management

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Kafka

Apache Flink

Apache Iceberg

Hive

Parquet

dbt

Fivetran

Airbyte

Apache Airflow

Snowflake

Amazon Redshift

Google BigQuery

AWS EMR

S3

Glue

Job description

Senior Data Engineer Job Requisition ID # 26WD100084

Position Overview

We are seeking an experienced Senior Data Engineer with 7+ years of expertise in designing, building, and optimizing scalable data platforms and pipelines. In this role, you will architect and develop robust data solutions that enable analytics, machine learning, and business intelligence across the organization. You will collaborate closely with Data Science, Machine Learning Engineering, Platform Engineering, Product, Analytics, and business stakeholders to build reliable, high-performance data ecosystems that deliver trusted, actionable insights. This role requires strong technical leadership, hands‑on engineering expertise, and the ability to influence data architecture and engineering best practices. Our culture emphasizes collaboration, innovation, continuous learning, and engineering excellence. We encourage ownership, knowledge sharing, and solving complex technical challenges while mentoring fellow engineers.

Key Responsibilities

• Design, develop, and maintain scalable, resilient, and high-performance data pipelines supporting batch and real-time workloads
• Build and optimize ETL/ELT pipelines for ingesting, transforming, validating, and serving large-scale datasets
• Design and implement robust data models, schemas, and storage strategies to ensure data quality, integrity, and accessibility
• Develop and optimize distributed data processing solutions using Spark, PySpark, SQL, and cloud-native technologies
• Integrate data from multiple enterprise systems while maintaining consistency, governance, and reliability
• Build and manage scalable data platforms using modern cloud services and data lake technologies
• Optimize database, warehouse, and pipeline performance for large-scale analytical workloads
• Implement monitoring, alerting, automated testing, and data quality validation across pipelines
• Establish and enforce data governance, security, compliance, and engineering best practices
• Partner with Product, Analytics, Data Science, Machine Learning, and Engineering teams to translate business requirements into scalable data solutions
• Enable self-service analytics by delivering trusted, well-modeled datasets
• Contribute to the technical roadmap by driving architecture discussions, defining engineering standards, and promoting reusable data platform components
• Mentor junior engineers through code reviews, technical guidance, and best practice adoption
• Maintain comprehensive technical documentation covering architecture, data models, workflows, and operational processes

Minimum Qualifications

• Bachelor's degree in computer science, Information Technology, Engineering, or a related field (or equivalent practical experience)
• 7+ years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Data Systems
• Strong hands‑on expertise in: Python Spark / PySpark Advanced SQL Shell scripting
• Strong understanding of relational databases such as PostgreSQL and MySQL
• Experience working with NoSQL databases including MongoDB, Cassandra, DynamoDB, or equivalent
• Solid understanding of data modeling, data architecture, and warehouse design principles
• Experience designing and operating scalable ETL/ELT pipelines across batch and streaming environments
• Hands‑on experience with modern data technologies such as: Apache Kafka Apache Flink Apache Iceberg Hive Parquet
• Experience using workflow orchestration platforms such as Apache Airflow
• Strong experience with cloud platforms, preferably AWS, including: EMR Glue S3 IAM Lambda Step Functions Athena Redshift
• Experience with modern data warehouse platforms such as Snowflake, Amazon Redshift, or Google BigQuery
• Experience implementing CI/CD pipelines, version control using Git, and infrastructure automation
• Experience implementing data validation, monitoring, incremental processing, backfills, reconciliation, and operational support for production pipelines
• Proven ability to lead technical initiatives, influence architecture decisions, establish engineering standards, and mentor engineering teams

Preferred Qualifications

• Experience with modern data transformation and ingestion tools such as dbt, Fivetran, Airbyte, or similar
• Experience building enterprise-scale data platforms supporting analytics, AI, and machine learning workloads
• Experience collaborating with Product Management, Design, Research, Analytics, and Machine Learning teams to build data products
• Familiarity with machine learning workflows, feature engineering, and MLOps concepts
• Experience in customer analytics, personalization, recommendation systems, or digital optimization
• Knowledge of real-time streaming architectures and event-driven data processing
• Experience working with Data Lakehouse architectures and open table formats
• Strong understanding of data governance, metadata management, lineage, and data catalog solutions
• Excellent communication, stakeholder management, and cross-functional collaboration skills
• Passion for continuous improvement, engineering excellence, and mentoring high-performing teams

Learn More About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk - it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk's competitive compensation package. Offers are based on the candidate's experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Belonging

We take pride in cultivating a culture of belonging where everyone can thrive.

Learn more here: https://www.autodesk.com/company/global-belonging

If you are an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).

Experience Level

Senior Level