Data Engineer
About this role
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.
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.
Frequently Asked Questions
Is the salary disclosed for the Data Engineer position at Weekday AI?
Where is the Data Engineer position at Weekday AI located?
Is the Data Engineer role at Weekday AI full-time or part-time?
Which team or department does the Data Engineer at Weekday AI belong to?
How do I apply for the Data Engineer position at Weekday AI?
When was the Data Engineer job at Weekday AI posted?
You'll be redirected to Weekday AI's official application page on workable.