permanent positionPosition: Data Analytics EngineerNexttec Technology is a leading outsourcing company that provides innovative and cutting-edge solutions to businesses worldwide. We are currently seeking a highly skilled and experienced Data Analytics Engineer to join our dynamic team on a full-time, permanent basis.As a Data Analytics Engineer, you will be responsible for designing, developing, and implementing data-driven solutions to help our clients make informed business decisions. You will work closely with our data scientists and business analysts to identify and understand business needs and translate them into technical requirements.Key Responsibilities:1. Power BI Semantic Layer Architect Design, build, and maintain high-performance Power BI semantic models.Develop complex DAX measures and calculated tables to fulfill business logic requirements.Implement advanced semantic modeling techniques (e.g., calculation groups, composite models) where appropriate.Optimize semantic models within the Microsoft Fabric ecosystem.2. Data Modeling & Business Logic CurationDefine and implement the business logic required to transform "Gold" layer data into high-performance semantic models.Collaborate with Data Engineers to ensure the Gold layer tables are structured optimally for Power BI consumption.Act as the primary gatekeeper for data definitions, ensuring that all metrics (e.g., Finance, Supply Chain, Sales) are standardized across the organization.Perform data validation and unit testing on DAX calculations to ensure the reliability of analytical outputs.Design and maintain certified, reusable semantic datasets to enforce a single source of truth across all reports.3. AI-Enabled Modeling & ProductivityLeverage AI-powered capabilities within Microsoft Fabric and Power BI (e.g., Copilot) to accelerate DAX authoring and model documentation.Optimize semantic models for Natural Language Querying (NLQ) by refining linguistic schemas, synonyms, and Q&A features.Utilize AI tools to generate initial analysis hypotheses and identify anomalies within the data models before reporting.Validate and refine AI-generated DAX or SQL logic to ensure strict alignment with approved business rules.4. Performance Optimization & GovernanceMonitor and troubleshoot performance bottlenecks specifically within the Power BI semantic layer and DAX queries.Implement and enforce Data Governance standards, including Row-Level Security (RLS) and Object-Level Security (OLS) within all models.Maintain comprehensive documentation of data models, measure definitions, and transformation logic.Support Data Analysts in adopting self-service BI by promoting the use of certified, standardized datasets.5. Collaboration with Business and IT TeamsCollaborate with Data Engineers to refine upstream data pipelines for downstream analytical consumption.Collaborate with BI teams to ensure data models align with reporting requirements and performance goals.Work with business stakeholders to understand their data needs and analytical requirements.Provide recommendations to optimize business processes based on analytical findings.6. Reporting and VisualizationSupport and guide Data Analysts in dashboard development; build dashboards when required for complex use cases to support business decision-making across domains (Finance, Procurement, Supply Chain, Sales etc.). 7. Data Quality and ValidationMonitor data quality and consistency, identifying and resolving discrepancies.Implement validation checks to ensure the reliability of analytical outputs.Support data governance initiatives by adhering to established standards and policies. 8. Documentation and Knowledge SharingDocument analytical methodologies, data sources, and semantic model specifications for reference.Share insights and best practices with team members to foster a data-driven culture.Maintain a repository of analytical assets for future use.Support business users in self-service BI, promote usage of standardized datasets. 9. Stay Updated on Analytical TrendsKeep abreast of advancements in data analytics, visualization tools, and industry best practices.Explore and recommend new tools or techniques to enhance analytical capabilities. 10. Support Business Intelligence InitiativesAssist BI teams in leveraging data for strategic decision-making.Provide analytical support for ad-hoc requests and long-term business intelligence projects.Education Required:Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.A Master's degree in a relevant field is an advantage but not mandatory.Certifications such as Microsoft Certified: Microsoft Certified: Fabric Analytics Engineer Associate (DP-600), Microsoft Certified: Power BI Data Analyst Associate (PL-300) preferredField of Experience:Data Modeling: Proven experience in building scalable, complex relational data models in Power BI.Advanced DAX: Expert-level proficiency in writing and optimizing DAX for large-scale datasets.Fabric Environment: Strong experience with Microsoft Fabric components. Data Processing: Basic understanding of ETL processes and data preparation techniques.Data Analysis: Proven experience in analyzing datasets and generating actionable insights.Data Visualization: Hands-on experience creating dashboards/visual representations of data.Database Querying: Hands-on experience in working with relational databases and querying tools.Stakeholder Collaboration: Proficiency translating business needs into analytical solutions.AI & Advanced Analytics: Exposure to AI-assisted analytics or automation tools in reporting and data analysis Years of Experience:5+ years of experience in data modeling, business intelligence, or analytics engineering.At least 3 years of hands-on experience focused specifically on Power BI development and DAX optimization. Technical Skills:Programming Languages: Proficiency in SQL for querying databases; advanced DAX and Power Query (M), familiarity with Python or R for data analysis and modeling is a plus.Data Visualization Tools: Advanced proficiency in Power BI. Tableau, Looker is a plus.Database Knowledge: Experience with relational databases (e.g. Oracle) Power BI: Advanced proficiency in Power BI, including dataflows, datasets, measures, and report development.Microsoft Fabric: Familiarity with Microsoft Fabric components (Data Warehouse, Lakehouse, OneLake, Data Pipelines) and their integration with Power BI.Architectures: Strong understanding of Star Schema design and the Medallion architecture (specifically the Gold layer)AI & Advanced Analytics: Familiarity with AI-assisted analytics tools such as Power BI Copilot, Natural language query features. Ability to use AI tools to enhance productivity while maintaining analytical accuracy.