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.
· Strong 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