Data Engineer (PySpark, SQL, Azure) - 8+ (Remote)

📍 Location: Remote (India)

💼 Type: Contract Full-Time (Immediate Joiners or 15 Days Notice Only)

⏳ Experience: Mid-Level to Senior (8+ Years)

Position Overview

We are seeking a highly skilled Data Engineer to design, build, and optimize next-generation data architecture and pipelines. This role requires expert-level proficiency in PySpark and SQL to build scalable, high-performance ETL/ELT processes that transform raw data into actionable insights.

Key Responsibilities

• Pipeline Development: Architect, develop, and maintain robust, fault-tolerant ETL/ELT pipelines for ingesting data from diverse sources.
• PySpark Expertise: Write and optimize complex data transformation jobs using PySpark and the Spark DataFrame API for large-scale data processing.
• SQL Mastery: Utilize Advanced SQL for complex querying, data manipulation, and performance tuning.
• Architecture & Automation: Design optimal data models (Dimensional Modeling, Snowflake Schema) and implement orchestration tools (e.g., Airflow, ADF).
• Quality & Collaboration: Implement data validation routines and collaborate closely with Data Scientists, Analysts, and stakeholders.

Required Technical Skills

• PySpark: Expert-level, hands-on experience in developing and optimizing large-scale data processing applications.
• SQL: Mastery of Advanced SQL (window functions, complex joins, query performance tuning) across platforms like Snowflake, Redshift, PostgreSQL.
• Programming & Big Data: Strong proficiency in Python/Pandas and solid understanding of distributed systems architecture.
• ETL/ELT: Proven experience in designing and maintaining robust data pipelines.

Preferred Qualifications

• Hands-on experience with major Cloud Platforms (specifically Azure data-related services).
• Familiarity with workflow orchestration tools (Apache Airflow) and streaming data (Kafka, Spark Structured Streaming).

📩 How to Apply: Send your resume to [email protected].

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