Senior Data Engineer | Remote
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Summary
Senior Data Engineer leading small-to-medium technical teams that design, build, and run cloud/hybrid data warehouses and pipelines on the Microsoft Azure data platform (Synapse, Data Factory, Data Lake, SQL), using Python, SQL, and PySpark. The role blends hands-on engineering with mentoring, technical decision-making, and client-facing work; AWS equivalents and Power BI are pluses.
Job Highlights
- Leadership Opportunities – This role will help you extend and expand your knowledge and experience in technical leadership positions. These include technical decisionmaking; guidance and mentorship of more junior team members; and developing relationships with project, client, and company leadership – all while remaining handson in your areas of expertise.
- Our technology focus is on Azure – you’ll have plenty of exciting opportunities to grow your skills in Microsoft and Azure in an environment committed to technical excellence and client experience in a very specific, defined space. Six months of experience on our team is worth years somewhere else.
- Microsoft Partnerships – Our great global relationship with Microsoft ensures that we have a pipeline of cutting‑edge Azure work opportunities, and access to the teams that have built the platform. You won’t find this at other places.
- Competitive compensation package, salary, allowance, standard benefits including quarterly and annual performance‑based cash bonus and other remuneration.
- Great working environment and company culture with flexible work location.
General Required Technical Skills:
- Experience leading small to medium sized technical teams (this includes work allocation/distribution to team members, technical escalation and support, representing the team in Agile ceremonies and client meetings).
- Expertise in designing and implementing logical and physical data models for cloud and hybrid data warehouse environments
- Implementing data architectures to support a variety of data formats and structures including structured, semi‑structured and unstructured data
- Experience with multiple full life‑cycle data warehouse implementations
- Understanding of data architectures required to support data integration processing
- Experience with data modeling technologies such as ER/Studio, ER/Win or similar
- Experience with Microsoft Azure Data Platform services including Azure Data Lake Store, Azure Storage, Azure Synapse, Azure Data Factory, Azure SQL database, Logic Apps, APIs
- Demonstrated ability to quickly learn, adopt and apply new technologies
- Data profiling and creation of source to target mappings
- Ability to provision and configure Azure data service resources
- With at least 5 - 8 years of relevant experience
Detailed Required Skills:
- Python & SQL Scripting
- SQL, PySpark
- General Cloud Architecture competency skillset - Capable of taking requirements and building out data pipelines
- API Knowledge is required, but preference given to candidates who can create APIs
Preferred Experience/Skills/Certifications
- Microsoft Fabric
- Microsoft Azure Cosmos DB, Data Flows, Express Route, Azure Active Directory
- Experience creating strategies to migrate customers from on-premise environments to Azure
- Power BI and semantic modeling
- AWS Glue & Azure Data Factory
- AWS S3 & Azure Blob
- AWS Athena & Azure Databricks
- AWS Redshift & Azure Synapse
- AWS ECS & Azure AKS