Azure Data Engineer

Overall Responsibilities

• Design and develop scalable, reliable data pipelines on Azure to collect, process, and store large datasets

• Implement efficient data models and data warehousing solutions aligning with business requirements

• Collaborate with data scientists, analysts, and application teams to integrate data workflows

• Optimize data pipeline performance, reliability, and security

• Support data governance, compliance, and data privacy standards

• Monitor operational health of data solutions and troubleshoot issues proactively

• Document architecture, workflows, and best practices for data ingestion and transformation

• Stay updated with the latest Azure data platform innovations and incorporate improvements

• Azure Data Factory, Azure Databricks, Azure Data Lake, Synapse Analytics

• Python, PySpark, Scala, or Java for data processing

• SQL, T-SQL, and experience with relational and non-relational data stores

Cloud & Infrastructure:

• Azure AI & Machine Learning services (optional)

• Azure Storage options: Blob, Data Lake, Cosmos DB

• Azure DevOps, CI/CD pipelines, Infrastructure as Code (ARM templates, Terraform)

Data Modeling & Warehousing:

• Star schema, data marts, normalization/denormalization principles

• Data governance, lineage, and security standards

Tools & Monitoring:

• Power BI, Azure Monitor, Log Analytics for data visualization and monitoring

• Version control systems like Git

• 5+ years of experience in data engineering, data architecture, or related roles

• Proven track record of designing and deploying data pipelines using Azure services

• Hands-on experience with cloud data solutions in a commercial or enterprise environment

• Experience working with cross-functional teams on large-scale data projects

• Familiarity with big data processing frameworks and emerging data technologies

• Develop, test, and deploy scalable data pipelines for ingestion, transformation, and storage

• Collaborate with data analysts, scientists, and stakeholders to understand data requirements

• Optimize ETL processes for performance, scalability, and cost-efficiency

• Monitor data pipeline health and troubleshoot issues proactively

• Implement data security, privacy, and governance measures

• Automate deployment workflows and manage infrastructure as code on Azure

• Document data architecture, workflows, and standards

• Stay current with new Azure data services and best practices to recommend improvements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field

• 5+ years of experience in data engineering, data architecture, or related disciplines

• Relevant Azure certifications (e.g., Microsoft Certified: Azure Data Engineer Associate) are preferred

Soft Skills:

• Strong problem-solving, analytical and organizational skills

• Excellent communication skills to interface with technical and non-technical stakeholders

• Ability to work independently and collaboratively in a team environment

• Attention to detail and commitment to data quality

• Adaptability to evolving technologies and project priorities

• Proactive mindset with continuous learning orientation

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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