Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities.
Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth.
Job DescriptionWe are looking for a skilled Data Engineer with 5+ years of experience to design, build, and maintain scalable data pipelines and platforms using Azure and Databricks. The ideal candidate will work closely with analytics, data science, and business teams to deliver reliable, high-performance data solutions that enable data-driven decision-making.
Key Responsibilities
- Design, develop, and optimize end-to-end data pipelines using Azure Databricks
- Build and maintain scalable ETL/ELT frameworks for structured and unstructured data
- Ingest data from multiple sources including APIs, databases, files, and streaming systems
- Work with Azure Data Lake Storage (ADLS Gen2) for efficient data storage and retrieval
- Develop data transformation logic using PySpark and Spark SQL
- Ensure data quality, reliability, and performance across pipelines
- Implement data modeling concepts to support analytics and reporting use cases
- Collaborate with Data Scientists, BI teams, and business stakeholders to understand data requirements
- Monitor, troubleshoot, and optimize Databricks jobs for performance and cost efficiency
- Apply best practices around security, governance, and compliance within Azure
- Participate in code reviews, documentation, and continuous improvement initiatives
- 5+ years of hands-on experience as a Data Engineer
- Strong experience with Azure Databricks
- Proficiency in PySpark, Spark SQL, and Python
- Experience working with Azure Data Lake Storage (ADLS Gen2)
- Solid understanding of data warehousing and data modeling concepts
- Experience building batch and/or streaming data pipelines
- Familiarity with Azure Data Factory or similar orchestration tools
- Strong SQL skills and experience with relational databases
- Experience using Git or similar version control systems
- Strong analytical, problem-solving, and communication skills
- Experience with Delta Lake
- Knowledge of streaming technologies (Kafka, Azure Event Hubs, Spark Structured Streaming)
- Exposure to CI/CD pipelines using Azure DevOps
- Experience working in Agile/Scrum environments
- Understanding of cloud cost optimization strategies
Skills Required
- 5+ years of hands-on experience as a Data Engineer
- Strong experience with Azure Databricks
- Proficiency in PySpark
- Proficiency in Spark SQL
- Proficiency in Python
- Experience with Azure Data Lake Storage (ADLS Gen2)
- Solid understanding of data warehousing and data modeling concepts
- Experience building batch and/or streaming data pipelines
- Familiarity with Azure Data Factory or similar orchestration tools
- Strong SQL skills and experience with relational databases
- Experience using Git or similar version control systems
- Apply best practices around security, governance, and compliance within Azure
- Strong analytical, problem-solving, and communication skills
- Experience with Delta Lake
- Knowledge of streaming technologies (Kafka, Azure Event Hubs, Spark Structured Streaming)
- Exposure to CI/CD pipelines using Azure DevOps
- Experience working in Agile/Scrum environments
- Understanding of cloud cost optimization strategies
Blend360 Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Blend360 and has not been reviewed or approved by Blend360.
-
Fair & Transparent Compensation — Pay is considered fair-to-good by many, and public salary postings for common data roles indicate competitive packages in numerous markets. Feedback suggests overall company sentiment aligns with acceptable compensation relative to peers in consulting and analytics.
-
Flexible Benefits — Flexible and remote/hybrid work arrangements are consistently highlighted in official materials and role descriptions. Feedback suggests flexibility is a meaningful part of the total rewards experience.
-
Retirement Support — A 401(k) with company match is part of the core package. Feedback suggests retirement offerings are standard and contribute to a complete benefits set.
Blend360 Insights
What We Do
Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. Blend360 has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace.
