Data Engineer

1 week ago


Delhi Division, India EGISEDGE TECHNOLOGIES PVT LTD Full time

Job Title :Data Engineer at Egisedge Technologies Pvt Ltd is a highly skilled role that involves designing, developing, and maintaining scalable ETL/ELT data pipelines using Databricks (PySpark) on Azure/AWS/GCP.Key Responsibilities :- Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks (PySpark) on Azure/AWS/GCP.- Develop clean, reusable, and performant Python code for data ingestion, transformation, and quality checks.- Write efficient and optimized SQL queries for querying structured and semi-structured data.- Work with stakeholders to understand data requirements and implement end-to-end data workflows.- Perform data profiling, validation, and ensure data quality and integrity.- Optimize data pipelines for performance, reliability, and integrate data from various sources APIs, flat files, databases, cloud storage e.g, S3, ADLS.- Build and maintain delta tables using Delta Lake format for ACID-compliant streaming and batch pipelines.- Work with Databricks Workflows to orchestrate pipelines and scheduled jobs.- Collaborate with DevOps and cloud teams to ensure secure, scalable, and compliant infrastructure.Technical Skills Required :Core Technologies :- Databricks Spark on Databricks, Delta Lake, Unity Catalog- Python with strong knowledge of PySpark- SQL Advanced level joins, window functions, CTEs, aggregationETL & Orchestration :- Databricks Workflows / Jobs- Airflow, Azure Data Factory, or similar orchestration tools- AUTO LOADER Structured Streaming preferredCloud Platforms Any one or more :- Azure Databricks on Azure, ADLS, ADF, Synapse- AWS Databricks on AWS, S3, Glue, Redshift- GCP Dataproc, BigQuery, GCSData Modeling & Storage :- Experience working with Delta Lake, Parquet, Avro- Understanding of dimensional modeling, data lakes, and lakehouse architecturesMonitoring & Version Control :- CI/CD pipelines for Databricks via Git, Azure DevOps, or Jenkins- Logging, debugging, and monitoring with tools like Datadog, Prometheus, or Cloud-native toolsOptional/Preferred :- Knowledge of MLflow, Feature Store, or MLOps workflows- Experience with REST APIs, JSON, and data ingestion from 3rd-party services- Familiarity with DBT Data Build Tool or Great Expectations for data qualitySoft Skills :- Strong analytical, problem-solving, and debugging skills- CLEAR communication and documentation skills- Ability to work independently and within cross-functional teams- Agile/Scrum working experience (ref:hirist.tech)


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