: Principal / Lead Data Engineer (PySpark, SQL)

Role & Requirements Overview

Exp: 10+ Years

Locations; 100% Remote

Role Overview

We are seeking a highly experienced and motivated Principal / Lead Data Engineer to join our dynamic data platform team in either our Gurgaon or Chennai office. The successful candidate will be a critical player in designing, building, and optimizing our next-generation data architecture and pipelines.

Key Responsibilities

Data Pipeline Development & Optimization

· Design and Build: Architect, develop, and maintain robust, scalable, and fault-tolerant ETL/ELT pipelines for ingesting data from diverse sources (e.g., databases, APIs, streaming sources) into our data lake and data warehouse.

· PySpark Expertise: Write and optimize complex data transformation jobs using PySpark and the Spark DataFrame API to process petabytes of structured and unstructured data efficiently.

Architecture and Infrastructure

· Data Modeling: Design and implement optimal data models (e.g., Dimensional Modeling, Data Vault, Snowflake Schema) for our data warehouse to support business intelligence and analytical needs.

· Cloud Integration: Drive cloud-native data solutions primarily leveraging Azure Databricks, Azure Data Lake, and Synapse (or comparable frameworks like AWS S3/Redshift and Google BigQuery) to build and deploy data solutions.

Required Technical Skills (Mandatory)

· Certification: Active Azure Databricks Certification (e.g., Databricks Certified Data Engineer Associate/Professional).

· PySpark: Expert-level, hands-on experience in developing, tuning,



and optimizing large-scale data processing applications using PySpark (Python for Apache Spark).

· SQL: Mastery of Advanced SQL (including window functions, complex joins, stored procedures, and query performance tuning) across various database systems (e.g., Snowflake, Redshift, PostgreSQL).

· Programming: Robust proficiency in Python for scripting, automation, and general data manipulation libraries (e.g., Pandas).

· Big Data Architecture: Deep understanding of Big Data concepts, distributed systems architecture, data lakes, and modern data warehousing principles.

· ETL/ELT: Proven experience in designing and implementing enterprise-grade ETL/ELT pipelines.

Preferred Qualifications (Good to Have)

· Hands-on experience with wider Azure ecosystem components (Azure Data Factory, Azure Synapse, Key Vault).

· Familiarity with workflow orchestration tools like Apache Airflow.

· Experience with real-time/streaming data processing (e.g., Spark Structured Streaming, Kafka, or Event Hubs).

· Advanced knowledge of Data Governance, Data Cataloging, and Data Security best practices.

Candidate Profile

· Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.

· Mindset: Proactive, self-motivated, strategic thinker with a strong sense of ownership and urgency.

· Communication: Excellent verbal and written communication skills to articulate complex technical concepts to non-technical stakeholders and executive leadership.

· Availability: Must be an Immediate Joiner or have a short notice period (7 days maximum).

📌 Lead Data Engineer (PySpark, SQL) (India)
🏢 solve IT consultant
📍 India