Lead Data Engineer

Fission Labs; Hyderabad; On-site; INR 3,800,000 - 6,800,000; Full time

Job summary

Fission Labs seeks a Lead/Senior Data Engineer to oversee data infrastructure design, development, and governance. You will lead a team of data engineers, architect scalable ETL pipelines, and collaborate with data scientists to meet business needs. Proficiency in Python, PySpark, SQL, and Databricks is essential.

You will drive data quality, security, and compliance while mentoring juniors and evaluating new technologies for enhanced data capabilities.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years of experience in data engineering, with at least 2 years in a leading project.
• Strong proficiency in Python, PySpark, and SQL.
• Extensive experience with Databricks and AWS cloud services.
• Hands-on experience with Airflow for workflow orchestration.
• Familiarity with FastAPI for building high-performance APIs.
• Experience with columnar databases like Rockset, Clickhouse, and CrateDB.
• Solid understanding of data modeling, data warehousing, and ETL processes.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Strong communication skills and ability to work effectively in cross-functional teams.
• Knowledge of data governance, security, and compliance best practices.
• Proficiency in designing and implementing data lake architectures using AWS S3.
• Experience with Databricks Unity Catalog or similar data governance and metadata management tools.

Responsibilities

• Lead the design, development, and maintenance of data pipelines and ETL processes architect and implement scalable data solutions using Databricks and AWS.
• Optimize data storage and retrieval systems using Rockset, Clickhouse, and CrateDB.
• Develop and maintain data APIs using FastAPI.
• Orchestrate and automate data workflows using Airflow.
• Collaborate with data scientists and analysts to support their data needs.
• Ensure data quality, security, and compliance across all data systems.
• Mentor junior data engineers and promote best practices in data engineering.
• Evaluate and implement new data technologies to improve the data infrastructure.
• Participate in cross-functional projects and provide technical leadership.
• Manage and optimize data storage solutions using AWS S3, implementing best practices for data lakes and data warehouses.
• Implement and manage Databricks Unity Catalog for centralized data governance and access control across the organization.

Skills

Python

PySpark

SQL

Databricks

AWS

Airflow

FastAPI

Rockset

Clickhouse

CrateDB

Data modeling

Data warehousing

ETL

Git

CI/CD

Education

Bachelor's or Master's degree in Computer Science / Engineering

Tools

Databricks

AWS

Rockset

Clickhouse

CrateDB

FastAPI

Airflow

Job description

Lead/Senior Data Engineer

is responsible for overseeing the design, development, and management of data infrastructure and pipelines within an organization. This role involves a mix of technical leadership, project management, and collaboration with other teams to ensure the efficient collection, storage, processing, and analysis of large datasets. The Lead Data Engineer typically manages a team of data engineers, architects, and analysts, ensuring that data workflows are scalable, reliable, and meet the businesss requirements.

Responsibilities

• Lead the design, development, and maintenance of data pipelines and ETL processes architect and implement scalable data solutions using Databricks and AWS.
• Optimize data storage and retrieval systems using Rockset, Clickhouse, and CrateDB.
• Develop and maintain data APIs using FastAPI.
• Orchestrate and automate data workflows using Airflow.
• Collaborate with data scientists and analysts to support their data needs.
• Ensure data quality, security, and compliance across all data systems.
• Mentor junior data engineers and promote best practices in data engineering.
• Evaluate and implement new data technologies to improve the data infrastructure.
• Participate in cross-functional projects and provide technical leadership.
• Manage and optimize data storage solutions using AWS S3, implementing best practices for data lakes and data warehouses.
• Implement and manage Databricks Unity Catalog for centralized data governance and access control across the organization.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 5+ years of experience in data engineering, with at least 2 years in a leading project
• Strong proficiency in Python, PySpark, and SQL
• Extensive experience with Databricks and AWS cloud services
• Hands-on experience with Airflow for workflow orchestration
• Familiarity with FastAPI for building high-performance APIs
• Experience with columnar databases like Rockset, Clickhouse, and CrateDB
• Solid understanding of data modeling, data warehousing, and ETL processes
• Experience with version control systems (e.g., Git) and CI/CD pipelines
• Excellent problem-solving skills and ability to work in a fast-paced environment
• Strong communication skills and ability to work effectively in cross-functional teams
• Knowledge of data governance, security, and compliance best practices
• Proficiency in designing and implementing data lake architectures using AWS S3
• Experience with Databricks Unity Catalog or similar data governance and metadata management tools

Nice To Have

• Experience with real-time data processing and streaming technologies
• Familiarity with machine learning workflows and MLOps
• Certifications in Databricks, AWS
• Experience implementing data mesh or data fabric architectures
• Knowledge of data lineage and metadata management best practices

Tech Stack

Databricks, Python, PySpark, SQL, Airflow, FastAPI, AWS (S3, IAM, ECR, Lambda), Rockset, CLickhouse, CrateDB