
Data Engineer
3 weeks ago
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, aggregation
ETL & Orchestration :
- Databricks Workflows / Jobs
- Airflow, Azure Data Factory, or similar orchestration tools
- AUTO LOADER Structured Streaming preferred
Cloud Platforms Any one or more :
- Azure Databricks on Azure, ADLS, ADF, Synapse
- AWS Databricks on AWS, S3, Glue, Redshift
- GCP Dataproc, BigQuery, GCS
Data Modeling & Storage :
- Experience working with Delta Lake, Parquet, Avro
- Understanding of dimensional modeling, data lakes, and lakehouse architectures
Monitoring & 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 tools
Optional/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 quality
Soft 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
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