Autodesk

1 day ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Design, build, and optimize scalable data pipelines and data platforms that power analytics, machine learning, and BI. Partner with Data Science, ML Engineering, Platform Engineering, Product, Analytics, and business stakeholders to deliver trusted, high-performance, self-service datasets. Lead architecture discussions, define engineering standards, and mentor engineers while implementing ETL/ELT, governance, monitoring, and data quality validation across batch and real-time workloads.

Location: Bengaluru

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design, develop, and maintain scalable, resilient, high-performance data pipelines for batch and real-time workloads.
•Build and optimize ETL/ELT pipelines to ingest, transform, validate, and serve large-scale datasets.
•Design and implement 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.
•Implement monitoring, alerting, automated testing, data quality validation, and enforce data governance, security, and compliance best practices.

Key Requirements

•Bachelor's degree in computer science, IT, engineering, or related field (or equivalent practical experience).
•7+ years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Data Systems.
•Hands-on expertise in Python, Spark/PySpark, and advanced SQL, plus shell scripting.
•Strong understanding of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
•Experience building scalable ETL/ELT pipelines across batch and streaming, with technologies such as Kafka, Flink, Iceberg, Hive, Parquet, and workflow orchestration (e.g., Airflow), plus AWS services (e.g., EMR, Glue, S3, IAM, Lambda, Step Functions, Athena, Redshift).

Experience:7+ years

Education:Bachelor's in computer science, Information Technology, Engineering, or related field

Skills:Technical leadershipHands-on engineeringStakeholder managementCross-functional collaborationMentoring

Tech Stack:PythonSparkPySparkSQLShell scriptingPostgreSQLMySQLNoSQLMongoDBCassandraDynamoDBApache KafkaApache FlinkApache IcebergHiveParquetApache AirflowAWSEMRGlue

Company Brief

Autodesk

Provides design and engineering software for architecture, construction, manufacturing, media, and entertainment industries, offering CAD, BIM, and 3D modeling tools to enable product and infrastructure design workflows.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Rafael, United States

Founded: 1982

Glassdoor: 3.9

Website LinkedIn Glassdoor

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Autodesk

1 day ago

Senior Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Bengaluru

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Design, develop, and maintain scalable, resilient, high-performance data pipelines for batch and real-time workloads.
•Build and optimize ETL/ELT pipelines to ingest, transform, validate, and serve large-scale datasets.
•Design and implement 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.
•Implement monitoring, alerting, automated testing, data quality validation, and enforce data governance, security, and compliance best practices.

Key Requirements

•Bachelor's degree in computer science, IT, engineering, or related field (or equivalent practical experience).
•7+ years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Data Systems.
•Hands-on expertise in Python, Spark/PySpark, and advanced SQL, plus shell scripting.
•Strong understanding of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
•Experience building scalable ETL/ELT pipelines across batch and streaming, with technologies such as Kafka, Flink, Iceberg, Hive, Parquet, and workflow orchestration (e.g., Airflow), plus AWS services (e.g., EMR, Glue, S3, IAM, Lambda, Step Functions, Athena, Redshift).

Experience:7+ years

Education:Bachelor's in computer science, Information Technology, Engineering, or related field

Skills:Technical leadershipHands-on engineeringStakeholder managementCross-functional collaborationMentoring

Tech Stack:PythonSparkPySparkSQLShell scriptingPostgreSQLMySQLNoSQLMongoDBCassandraDynamoDBApache KafkaApache FlinkApache IcebergHiveParquetApache AirflowAWSEMRGlue

Company Brief

Autodesk

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Rafael, United States

Founded: 1982

Glassdoor: 3.9

Website LinkedIn Glassdoor