Cloud Platforms Data Engineer Data Analysis
A. Data Analysis & Insights • Identify trends and patterns in large datasets. • Provide actionable insights to support strategic and operational business decisions. • Conduct ad-hoc and deep-dive analyses for various business units. B. Data Systems & Integrity • Maintain and manage data collection systems and databases. • Ensure data integrity, accuracy, and availability. • Collaborate with data governance teams to uphold data quality, lineage, and security protocols. C. Data Visualization & Reporting • Develop interactive dashboards and reports for stakeholders. • Communicate findings and recommendations clearly to technical and non-technical audiences. • Use visualization tools to support strategic planning and performance tracking. D. Experimentation & Advanced Analytics • Design and analyze experiments to validate business hypotheses. • Interpret results to guide product development and strategic initiatives. • Build models and perform advanced analytics to uncover hidden insights. E. Cross-Functional Partnership • Partner with business leaders to define KPIs and success metrics. • Serve as a strategic advisor to teams in marketing, finance, operations, and product. • Support business teams with data modeling and advanced analytics. F. Data Engineering & Automation • Collaborate with data engineers to implement CI/CD pipelines for analytics assets. • Work with analytics engineers and data scientists to design robust data models and pipelines. • Ensure reproducibility, scalability, and collaboration across analytics projects. G. Enablement & Mentorship • Mentor business users in self-service analytics tools and data literacy. • Promote a data-driven culture across the organization.
Education • Bachelor’s degree in Computer Science, Information Technology, Information Systems, or any field with an emphasis on computing and IT with quantitative techniques. Experience • At least 5 years of experience in data analysis, data engineering, data science, or a related field such as software engineering. Certifications • Relevant certifications such as Microsoft Certified: Power BI Data Analyst Associate, Databricks Certified Data Engineering Associate, Microsoft Certified Fabric Analytics Engineer, or Microsoft Fabric Data Engineer. Technical Skills • Data Analysis: Proficiency in analyzing large complex data sets using statistical methods and tools. • Data Engineering: Experience with ETL/ELT processes to move and transform data; ability to develop, construct, test, and maintain data pipelines. • Cloud Platforms: Experience with cloud services, specifically Azure for scalable data solutions and the Databricks analytics platform. • Tools and Software: Proficiency in tools such as SQL, Python, Power BI. • Database Management and Data Modelling: Proficiency in data modelling, schema design, and applying industry-standard methodologies to structure enterprise-wide warehouses and subject area marts that provide consistency, availability, and scalability. • Business Acumen: Ability to translate business requirements into data analysis tasks and provide insights that drive strategic decisions. • Data Management: Experience implementing metadata management tools; exposure to Azure Purview / Databricks Unity Catalog for lineage, data discovery, and enhancing governance and transparency. • Data Ops: Experience with Git, code deployment workflows for BI tools and data transformation scripts. Experience monitoring data pipeline performance and implementing alerting systems for analytical workloads. Soft Skills • A proactive, detail-oriented individual who is curious and passionate about data. • Team player with strong interpersonal skills. • Analytical Thinking: Strong problem-solving skills and the ability to think critically about data. • Communication: Excellent verbal and written communication skills to effectively present findings and insights. • Attention to Detail: High level of accuracy and attention to detail in data analysis and reporting. • Collaboration: Ability to work well with cross-functional teams and stakeholders. • Adaptability: Flexibility to adapt to changing business needs and priorities.
• Benefits will be shared in detail with successful candidates.
