About Senzcraft:
Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies.
We have a suite of SaaS products and services, partnering with automation product companies.
Please visit our website - https://www.senzcraft.com for more details
- Our AI Operations SaaS platform – https://MagicOps.ai
- Senzcraft on linkedin -> https://www.linkedin.com/company/senzcraft
Senzcraft is awarded by Analytics India Magazine in it's report State of AI in India as a Niche AI startup. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.
About the Opportunity:
We are looking for a highly skilled Senior Data Engineer to design, develop, and maintain scalable data platforms and pipelines. The ideal candidate will have strong expertise in Google Cloud Platform (GCP), Data Engineering, and Apache Spark, with the ability to build robust data solutions that support analytics, reporting, and business intelligence initiatives.
Experience: 5-8 Years
Location: Bangalore (Hybrid)
Key Responsibilities:
- Design, develop, and optimize scalable ETL/ELT data pipelines.
- Build and maintain cloud-native data solutions using Google Cloud Platform (BigQuery, Dataflow).
- Develop and optimize large-scale data processing applications using Apache Spark.
- Create and maintain data models, data warehouses, and data lakes to support business requirements.
- Write and optimize complex SQL queries for data transformation, reporting, and analytics.
- Implement data quality, governance, and monitoring processes.
- Collaborate with cross-functional teams including Data Analysts, Data Scientists, and Business Stakeholders.
- Support batch and real-time data processing solutions using Kafka, Spark Streaming, or similar technologies.
- Participate in code reviews, performance tuning, and best practice implementation.
- Contribute to CI/CD processes and automation of data workflows.
Mandatory Skills:
Google Cloud Platforms (GCP)
- Hands-on experience with BigQuery and Dataflow.
- Experience building cloud-native data pipelines and analytics solutions.
Data Engineering
- Strong experience designing and implementing ETL/ELT pipelines.
- Knowledge of data warehousing, data lakes, and modern data architecture.
Apache Spark& SQL
- Extensive experience with Apache Spark for large-scale data processing.
- Advanced SQL skills including joins, window functions, CTEs, and query optimization.
Required Technical Skills:
- Programming: Python, Java, or Scala
- SQL: Advanced querying and performance tuning
- Apache Spark
- BigQuery
- Dataflow
- Data Warehousing Concepts
- Data Lakes & Lakehouse Architecture
- Git and Version Control
- CI/CD Pipelines
Preferred Skills:
- Kafka, Apache Flink, or Spark Streaming
- AWS (S3, Redshift, Glue, Lambda)
- Azure (Data Factory, Synapse)
- Docker and Kubernetes
- DataOps Practices
- Real-Time Analytics Systems
- API Integration
- Machine Learning Pipeline Support
