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Data Engineer

๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐—ผ๐—น๐—ฒ ๐—ถ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐—ฒ๐—ธ๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€

๐—ฆ๐—ฎ๐—น๐—ฎ๐—ฟ๐˜† ๐—ฟ๐—ฎ๐—ป๐—ด๐—ฒ: ๐—ฅ๐˜€ ๐Ÿณ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ - ๐—ฅ๐˜€ ๐Ÿญ๐Ÿฑ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ (๐—ถ๐—ฒ ๐—œ๐—ก๐—ฅ ๐Ÿณ-๐Ÿญ๐Ÿฑ ๐—Ÿ๐—ฃ๐—”)

Experience: 2+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for a skilled Data Engineer 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 on 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 using GCP, Databricks, or other major cloud platforms.
  • Build data processing and transformation solutions using Python, SQL, Spark, and PySpark.
  • Develop and manage data workloads using Databricks Notebooks and Workflows.
  • Work extensively with BigQuery and Google Cloud Storage 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 Engineering or a closely related role.
  • Strong practical knowledge of at least one major cloud platform such as GCP, Azure, or AWS.
  • Hands-on experience with Databricks, BigQuery, and cloud storage technologies.
  • Strong proficiency in Python and SQL.
  • Solid understanding of ETL/ELT processes, data pipelines, and data warehousing concepts.
  • Experience working with both structured and unstructured data.
  • Familiarity with Apache Airflow or Cloud Composer.
  • Exposure to Azure Data Factory (ADF) is an advantage.
  • Knowledge of Git, CI/CD, and Agile development methodologies.
  • Exposure to Kafka, Google Pub/Sub, or other streaming technologies 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.

See also

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