We are looking for a Data Engineer with 2-5 years of experience to design, build, and maintain reliable data pipelines and analytics-ready datasets. The ideal candidate will have strong SQL and Python or PySpark skills, hands-on experience with cloud data platforms, and the ability to troubleshoot data-quality, performance, and production issues independently.

Key Responsibilities

- Design, develop, and maintain scalable ETL and ELT pipelines for batch and scheduled data processing

- Build and optimize data transformations using SQL, Python, and PySpark

- Ingest and integrate data from databases, APIs, files, SharePoint, and cloud storage

- Create and maintain curated, analytics-ready datasets for Power BI, Superset, and other reporting platforms

- Implement data-quality checks, reconciliation controls, monitoring, logging, and failure alerts

- Troubleshoot pipeline failures, schema mismatches, performance bottlenecks, and data discrepancies

- Optimize large-scale data processing for runtime, memory, storage, and cost efficiency

- Automate recurring workflows and schedule production jobs using orchestration tools such as Apache Airflow

- Maintain technical documentation, data mappings, business rules, and operational runbooks

- Collaborate with BI analysts, application teams, and business stakeholders to deliver dependable data solutions

Requirements

Required Skills and Experience





- 2-5 years of professional experience in data engineering, ETL development, or a similar role

- Solid SQL skills, including joins, common table expressions, window functions, data validation, and query optimization

- Hands-on experience with Python and/or PySpark for data processing and automation

- Practical experience building and supporting ETL or ELT pipelines in production

- Experience working with large datasets, incremental loads, upserts, schema changes, and partitioned data

- Good understanding of relational databases, dimensional modeling, data warehousing, and file formats such as Parquet, CSV, and JSON

- Experience with Git or another version-control system and structured deployment practices

- Strong debugging, analytical, documentation, and stakeholder-communication skills

Preferred Skills

- Experience with AWS services such as Amazon S3, Athena, EMR, and EMR Serverless

- Experience with Apache Spark, Delta Lake, Apache Airflow, Dremio, or Trino-compatible SQL engines

- Familiarity with Power BI, Apache Superset, or other downstream reporting tools

- Experience with REST APIs, SharePoint integrations, and automated file-delivery workflows

- Understanding of data security, access controls, privacy, and production monitoring practices

Benefits

- 5 Days working

- Remote Job

- Medical Insurance

📌 Data Engineer (Gurugram)
🏢 Sago
📍 Gurugram