Onebridge is seeking a highly skilled Data Engineer to design and build scalable data pipelines and analytics solutions using Microsoft Azure services. The ideal candidate will thrive in data-rich environments, solving complex challenges related to data ingestion, transformation, and performance optimization while collaborating across teams to deliver clean, reliable, and actionable data.
What You'll Do
- Design and develop data pipelines using Azure services (e.g., Azure Data Factory, Azure Databricks, Azure Synapse Analytics) to support analytics, reporting, and machine learning use cases.
- Build scalable ETL/ELT workflows that ingest, transform, and load data from various sources into Azure Data Lake and cloud-based data warehouses.
- Optimize performance and reliability of data processing jobs, ensuring efficient resource usage and minimal latency.
- Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver high-quality solutions.
- Implement data quality checks, monitoring, and alerting to ensure accuracy and consistency across datasets.
- Support deployment and automation using CI/CD pipelines, version control (Git), and infrastructure-as-code tools.
What We're Looking For
- 5+ years of experience in data engineering or related roles, with a strong focus on cloud-based data platforms and large-scale data processing.
- Hands-on experience with Microsoft Azure services such as Azure Databricks, Azure Data Factory, Azure Data Lake Storage, and Azure Synapse Analytics.
- Proficiency in Python, SQL, and data transformation techniques.
- Strong understanding of distributed data processing frameworks (e.g., Apache Spark) and performance optimization.
- Familiarity with CI/CD tools, Git, and DevOps practices in cloud environments.
- Knowledge of data modeling and performance tuning, with the ability to troubleshoot and optimize complex data workflows.
Technical Stack
Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage, Python, SQL, Apache Spark, Git, CI/CD, ETL, ELT, distributed computing, cloud-native data engineering, infrastructure-as-code
Work Mode
This role operates in a hybrid model, requiring presence onsite for two days per week in one of the following locations: Bangalore, Pune, Hyderabad, or Chennai.
