Data Engineer
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ณ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ญ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ณ-๐ญ๐ฑ ๐๐ฃ๐)
Experience: 2+ yrs
Location: Bengaluru, Karnataka, India
Job Type: Full-time
We are looking for a skilledย Data Engineerย to design, build, and support modern cloud-based data solutions. This role is ideal for someone who enjoys working with large and complex datasets, developing reliable data pipelines, and transforming raw data into high-quality, analytics-ready information.
You will work across cloud platforms and modern data engineering technologies, with a strong focus onย GCP, Databricks, BigQuery, Python, SQL, and Spark/PySpark. You will collaborate closely with data engineers, architects, BI teams, and other technical stakeholders to build scalable data platforms that support reporting, analytics, and business decision-making.
The role offers an opportunity to work across batch and near-real-time data processing while contributing to data quality, platform reliability, and continuous improvements in engineering practices.
Requirements
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ingestion workflows usingย GCP, Databricks, or other major cloud platforms.
- Build data processing and transformation solutions usingย Python, SQL, Spark, and PySpark.
- Develop and manage data workloads usingย Databricks Notebooks and Workflows.
- Work extensively withย BigQuery and Google Cloud Storageย for data storage and processing.
- Support scheduled, batch, and near-real-time data ingestion and processing requirements.
- Develop reliable ETL/ELT workflows while following data engineering and data warehousing best practices.
- Implement monitoring, validation, and quality checks to ensure pipeline reliability and data accuracy.
- Prepare and maintain high-quality datasets for BI, reporting, and analytics teams.
- Collaborate with engineers and architects to improve data platforms, architecture, and engineering practices.
- Troubleshoot data pipeline issues and optimize workloads for performance and scalability.
- Follow established development, version-control, CI/CD, and Agile practices.
What Makes You a Great Fit
- 2+ years of hands-on experience in Data Engineeringย or a closely related role.
- Strong practical knowledge of at least one major cloud platform such asย GCP, Azure, or AWS.
- Hands-on experience withย Databricks, BigQuery, and cloud storage technologies.
- Strong proficiency inย Python and SQL.
- Solid understanding ofย ETL/ELT processes, data pipelines, and data warehousing concepts.
- Experience working with both structured and unstructured data.
- Familiarity withย Apache Airflow or Cloud Composer.
- Exposure toย Azure Data Factory (ADF)ย is an advantage.
- Knowledge ofย Git, CI/CD, and Agile development methodologies.
- Exposure toย Kafka, Google Pub/Sub, or other streaming technologiesย is a plus.
- Strong analytical and problem-solving abilities with a proactive approach to troubleshooting.
- Good communication skills and the ability to collaborate effectively with technical and cross-functional teams.
- A strong sense of ownership and enthusiasm for learning and working with modern cloud and data technologies.