Software Engineer III - Data Engineer
JPMorgan Chase & Co.
Mumbai 2 months ago 57 views
Full-time On-site Mid Level Technology
Data & Analytics
Data Engineer Career Path
Build the pipelines that move and transform data. Data engineers create the infrastructure that makes analytics and ML possible.
4 career levels
$60K-$80K → $170K-$250K+
Career Ladder
1
Entry Level
Junior Data Engineer
$60K-$80K
0-2 years
Build basic pipelines, write SQL transformations, learn warehouse design.
Day-to-Day Responsibilities
- Apply SQL and Python in daily work
- Collaborate with team members on data & analytics initiatives
- Build expertise in ETL basics, Data Warehousing
- Document processes and contribute to team knowledge base
- Meet entry-level performance expectations and deliverables
Skills Required
SQLPythonETL basicsData WarehousingCloud basics (AWS/GCP)Git
What to Focus On
At the entry level, focus on building strong foundations in SQL, Python, ETL basics. Understand the fundamentals deeply before moving to advanced topics. Build basic pipelines, write SQL transformations, learn warehouse design.
How to Advance to Data Engineer
To advance from Junior Data Engineer to Data Engineer, you need to demonstrate mastery of SQL, Python, ETL basics and start developing skills in Spark/Databricks, Airflow/dbt. Take on stretch assignments, seek mentorship, and build a track record of consistent delivery.
2
Mid Level
Data Engineer
$85K-$130K
2-5 years
Build production pipelines, implement data models, ensure data quality.
Day-to-Day Responsibilities
- Apply Spark/Databricks and Airflow/dbt in daily work
- Collaborate with team members on data & analytics initiatives
- Build expertise in Data Modeling, Streaming (Kafka)
- Document processes and contribute to team knowledge base
- Meet mid-level performance expectations and deliverables
Skills Required
Spark/DatabricksAirflow/dbtData ModelingStreaming (Kafka)Cloud Data ServicesData Quality
What to Focus On
At the mid level, focus on building strong foundations in Spark/Databricks, Airflow/dbt, Data Modeling. Deepen your expertise and start developing leadership skills. Build production pipelines, implement data models, ensure data quality.
How to Advance to Senior Data Engineer
To advance from Data Engineer to Senior Data Engineer, you need to demonstrate mastery of Spark/Databricks, Airflow/dbt, Data Modeling and start developing skills in Data Platform Architecture, Real-time Processing. Take on stretch assignments, seek mentorship, and build a track record of consistent delivery.
3
Senior Level
Senior Data Engineer
$130K-$175K
5-8 years
Architect data platforms, build real-time systems, lead data infrastructure.
Day-to-Day Responsibilities
- Apply Data Platform Architecture and Real-time Processing in daily work
- Collaborate with team members on data & analytics initiatives
- Build expertise in Data Governance, Cost Optimization
- Document processes and contribute to team knowledge base
- Meet senior-level performance expectations and deliverables
Skills Required
Data Platform ArchitectureReal-time ProcessingData GovernanceCost OptimizationTeam MentoringML Pipelines
What to Focus On
At the senior level, focus on building strong foundations in Data Platform Architecture, Real-time Processing, Data Governance. Deepen your expertise and start developing leadership skills. Architect data platforms, build real-time systems, lead data infrastructure.
How to Advance to Staff/Principal Data Engineer / Head of Data
To advance from Senior Data Engineer to Staff/Principal Data Engineer / Head of Data, you need to demonstrate mastery of Data Platform Architecture, Real-time Processing, Data Governance and start developing skills in Data Strategy, Platform Leadership. Take on stretch assignments, seek mentorship, and build a track record of consistent delivery.
4
Lead Level
Staff/Principal Data Engineer / Head of Data
$170K-$250K+
8+ years
Define data strategy, lead platform teams, architect org-wide data systems.
Day-to-Day Responsibilities
- Apply Data Strategy and Platform Leadership in daily work
- Collaborate with team members on data & analytics initiatives
- Build expertise in Cross-org Data Architecture, Data Mesh/Fabric
- Document processes and contribute to team knowledge base
- Meet lead-level performance expectations and deliverables
Skills Required
Data StrategyPlatform LeadershipCross-org Data ArchitectureData Mesh/FabricExecutive Communication
What to Focus On
At the lead level, focus on building strong foundations in Data Strategy, Platform Leadership, Cross-org Data Architecture. Deepen your expertise and start developing leadership skills. Define data strategy, lead platform teams, architect org-wide data systems.
Open Data Engineer Positions
Frequently Asked Questions
What skills do I need to become a Junior Data Engineer?
Key skills for Junior Data Engineer (0-2 years): SQL, Python, ETL basics, Data Warehousing, Cloud basics (AWS/GCP), Git. Build basic pipelines, write SQL transformations, learn warehouse design.
What skills do I need to become a Data Engineer?
Key skills for Data Engineer (2-5 years): Spark/Databricks, Airflow/dbt, Data Modeling, Streaming (Kafka), Cloud Data Services, Data Quality. Build production pipelines, implement data models, ensure data quality.
What skills do I need to become a Senior Data Engineer?
Key skills for Senior Data Engineer (5-8 years): Data Platform Architecture, Real-time Processing, Data Governance, Cost Optimization, Team Mentoring, ML Pipelines. Architect data platforms, build real-time systems, lead data infrastructure.
What skills do I need to become a Staff/Principal Data Engineer / Head of Data?
Key skills for Staff/Principal Data Engineer / Head of Data (8+ years): Data Strategy, Platform Leadership, Cross-org Data Architecture, Data Mesh/Fabric, Executive Communication. Define data strategy, lead platform teams, architect org-wide data systems.
What is the salary range for a Data Engineer?
Data Engineer salaries range from $60K-$80K at entry level to $170K-$250K+ at the Lead level.