At ProArch, we partner with businesses around the world to turn big ideas into better outcomes through IT services that span cybersecurity, cloud, data, AI, and app development. We’re 400+ team members strong across 3 countries (we call ourselves ProArchians)—and here’s what connects us all:
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A love for solving real business problems
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A belief in doing what’s right
What’s it like to work here?
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You’ll keep growing. You’ll work alongside domain experts who love to share what they know.
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You’ll be supported, heard, and trusted to make an impact.
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You’ll take on projects that touch industries, communities, and lives.
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You’ll have the time to focus on what matters most in your life outside of work.
At ProArch, you’ll be part of teams that design and deliver technology solutions solving real business challenges for our clients. With services spanning AI, Data, Application Development, Cybersecurity, Cloud & Infrastructure, and Industry Solutions, your work may involve building intelligent applications, securing business‑critical systems, or supporting cloud migrations and infrastructure modernization.
Every role here contributes to shaping outcomes for global clients and driving meaningful impact. You’ll collaborate with experts across data, AI, engineering, cloud, cybersecurity, and infrastructure—solving complex problems with creativity, precision, and purpose. You’ll join a culture rooted in technology, curiosity, and continuous learning. A place where we move fast, trust you to make an impact, encourage innovation, and support your growth.
Job Summary:
ProArch is seeking a Senior Data Engineer with 5–8 years of experience to join our Data & Analytics practice. In this role, you will design, develop, and optimize scalable cloud-based data solutions that support enterprise analytics, reporting, and AI initiatives. You will work with large-scale datasets using Azure Data Platform technologies, build high-performance data pipelines, and collaborate directly with business and client stakeholders to deliver reliable, secure, and scalable data solutions.
The ideal candidate has strong expertise in SQL, Python, Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, and Microsoft Fabric (preferred), along with solid experience in data modelling, DataOps, and client-facing engagements.
Responsibilities:
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Design, develop, and optimize scalable data pipelines using Azure Synapse Analytics, Spark Pools, Azure Data Factory (ADF), and Azure Data Lake.
- Develop high-performance solutions using SQL and Python, ensuring scalability, maintainability, and optimized query performance.
- Build and manage modern data platforms on Microsoft Azure, supporting structured and unstructured data ingestion at enterprise scale.
- Design and implement robust data models, including dimensional modelling and Slowly Changing Dimensions (SCD), to support reporting and analytics.
- Optimize data partitioning, indexing, storage, versioning, and compute costs for large-scale cloud workloads.
- Implement CI/CD pipelines and adopt DataOps best practices for automated deployment, testing, and monitoring.
- Ensure data quality through unit testing, validation frameworks, and automated quality checks.
- Collaborate directly with clients, business stakeholders, architects, and cross-functional teams to gather requirements, design solutions, and provide technical guidance.
- Troubleshoot production issues, perform root cause analysis, and recommend performance improvements.
- Mentor junior engineers by promoting engineering best practices, code quality, and technical excellence.
Requirements
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Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field.
- 5–8 years of experience in Data Engineering with strong expertise in enterprise cloud data platforms.
- Strong hands-on experience with SQL and Python, including performance tuning and optimization.
- Extensive experience with Azure Synapse Analytics, Azure Data Factory (ADF), Azure Data Lake, and other Azure data services.
- Good understanding of Microsoft Azure architecture and cloud-native data engineering practices.
- Experience with Microsoft Fabric is preferred.
- Strong evidence of data modelling expertise, including dimensional modelling, star/snowflake schemas, Slowly Changing Dimensions (SCD), and data warehouse design.
- Experience working with large-scale datasets involving high volume, velocity, and variety.
- Hands-on experience implementing CI/CD pipelines and DataOps practices.
- Strong analytical and troubleshooting skills with a focus on performance optimization.
- Excellent communication skills with proven experience working directly with clients, understanding business requirements, conducting technical discussions, and delivering customer-focused solutions.
Good to Have Skills:
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Experience with Microsoft Fabric, Lakehouse, and OneLake.
- Knowledge of Delta Lake, versioned data, and advanced partitioning strategies.
- Experience implementing data governance, security, and compliance frameworks.
- Exposure to cloud cost optimization strategies across storage and compute.
- Experience with Spark performance tuning and distributed data processing.
- Familiarity with Power BI integration and enterprise analytics platforms.
- Experience mentoring junior engineers or leading technical initiatives.
