Data Engineer
Job Description
About the Role
We are looking for a highly skilled Data Engineer with strong Google Cloud Platform (GCP) expertise to design, develop, and maintain scalable data solutions. The ideal candidate will have hands-on experience in building robust ETL/ELT frameworks, real-time and batch data pipelines, data modeling, and leveraging modern GCP services to support analytics and business intelligence initiatives.
Key Responsibilities
- Design, develop, and optimize scalable data pipelines on GCP.
- Build and maintain batch, event-driven, and real-time data ingestion and processing frameworks.
- Develop robust ETL/ELT pipelines for integrating data from multiple internal and external sources.
- Design and implement efficient data models to support reporting, analytics, and data science use cases.
- Create and manage data orchestration workflows using Cloud Composer (Apache Airflow).
- Develop event-driven architectures using Pub/Sub, Cloud Functions, and other cloud-native services.
- Optimize data storage, transformation, and querying performance using BigQuery.
- Ensure data quality, consistency, governance, and security best practices.
- Collaborate with Data Analysts, Data Scientists, Architects, and business stakeholders to translate requirements into scalable solutions.
- Monitor, troubleshoot, and improve data platform performance and reliability.
Required Skills & Experience
GCP Services (Must Have)
Hands-on experience with one or more of the following GCP services:
- BigQuery
- Cloud Composer (Airflow)
- Pub/Sub
- Cloud Functions
- Cloud Storage
- Dataflow
- Cloud Run (good to have)
Core Technical Skills
- Strong experience in designing and implementing data models (Star Schema, Snowflake Schema, Dimensional Modeling).
- Proven experience in building and maintaining ETL/ELT pipelines.
- Expertise in developing:
- Batch-based data pipelines
- Event-driven data pipelines
- Real-time/streaming data pipelines
- Advanced SQL skills with performance tuning experience.
- Strong Python programming experience for data engineering workflows.
- Experience working with structured and semi-structured data formats (JSON, Parquet, Avro, CSV).
- Knowledge of data warehousing concepts and best practices.
More Info
Key Skills
About Company
Skills:
snowflake , Azure Databricks, Json, ELT, Data Integration, Excel, Data Modelling, Azure DevOps, Apis, Csv, Data Warehousing, Sql, Git, Azure Data Factory, Powerbi, Xml, Etl, GenAI use cases, PDFs, AI-assisted data processing workflows, Data pipelines, Data ingestion frameworks, Data Analysis, ADLS Gen2, Vector search embeddings, Synapse, AI ML concepts, CI CD pipelines
Skills:
T-sql, Query Optimization, Backup And Recovery, Sql Server Administration, Performance Tuning, Execution Plans, Statistics, Production Support, Indexing
Skills:
snowflake , Data Warehousing, Kafka, Automated Testing, ELT, Docker, Python, Azure DevOps, AWS, Data Modelling, Sql, Devops, Data Quality, Git, Databricks, Kubernetes, Etl, data lakes, Security, MDM, Event Hubs, metadata lineage, production reliability, GitHub Enterprise, DataOps, dbt, CI CD pipelines
Skills:
Nosql, Erwin, Hadoop, Data Modeling, Business Requirements Analysis, Big Data Technologies, Data Warehousing, Etl, MDM, data integrity, Advanced Data Modeling
Skills:
Java, Hadoop, Cassandra, Scala, Spark, Dynamodb, Kafka, Sql, ELT, Devops, Hive, Agile, MongoDB, Hbase, Etl, Data Lakes, Accumulo, Map-Reduce