Job Roles and Responsibilities
• Review and assess the current data platform architecture, identifying gaps, risks, and optimization opportunities.
• Architect and design scalable, real-time data solutions aligned with business and operational needs.
• Partner with business leaders across Finance, Accounting, Sales, and Operations to translate data requirements into technical solutions.
• Build and maintain a modern, cloud-based data environment supporting enterprise analytics and AI initiatives.
• Lead data engineering initiatives using SQL, Python, Databricks, Snowflake, and modern ELT/streaming patterns.
• Apply data science methodologies using Python, Dataiku, and statistical modeling techniques.
• Design and deploy machine learning pipelines, supporting model training, deployment, monitoring, and lifecycle management.
• Serve as Data Governance SME, leveraging Alation for metadata management, cataloguing, lineage, and stewardship.
• Administer Alation platform including user roles, permissions, workflows, policies, and automation.
• Manage self-hosted Alation installations on Azure, including VM management, networking, firewalls, patching, and HA configurations.
• Monitor Alation platform health, performance, usage, and implement upgrades and enhancements.
• Collaborate with data stewards and governance teams to enforce data quality, metadata, security, and access standards.
• Provide L1/L2 support for Alation users, delivering onboarding, training, documentation, and adoption programs.
• Develop dashboards and executive-ready analytics using Power BI, Tableau, and Microsoft analytics tools.
• Implement cloud-native solutions leveraging AWS (S3, Redshift, Glue, SageMaker) and Azure (Fabric, ADF, Synapse, SQL, Power BI).
• Ensure compliance with security, privacy, disaster recovery, testing, and DevOps best practices across cloud platforms.
• Act as technical or team lead, overseeing delivery, mentoring engineers, and ensuring high-quality outcomes.
• Produce architectural designs, solution documentation, and knowledge-based artifacts for reuse and governance.
• Contribute as a Centre of Excellence member, Microsoft Certified Trainer, and cloud/AI SME, coaching teams and driving continuous capability growth.
Technical Skills:
SQL, Python, Pyspark, Snowflake, Databricks, Tableau, Power BI, Qlikview and other BI tools, Github, Airflow, API’s, AWS (S3, IAM, Redshift, Cloudwatch, Glue, Sagemaker,etc..), Azure ( Microsoft Fabric, Azure Data Factory, SQL Server, Azure, QL,SSAS,Synapse,Power BI) Data Governance - Alation , AXON, Informatica Cloud, DBT, Devops and testing, EDW , Data Lakes, Data Science , Machine Learning and AI.
Education: The minimum qualification required for performing the above specialty occupation duties is a bachelor's degree or equivalent in Computer Science or equivalent in a related field or a foreign equivalent is required closely related field with relevant experience.