Data Engineer / Data Analyst - SQL, Power BI & Data Warehousing

Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or related fields
• Relevant certifications in SQL Server, Power BI, Azure Data Fundamentals, or equivalent (preferred)
• Professional experience in financial services or index & analytics domain is highly advantageous
• Professional Competencies
• Strong analytical and problem-solving skills with an eye for detail
• Excellent communication skills for engaging with technical and non-technical stakeholders
• Ability to work independently and collaboratively in a fast-paced environment
• Adaptability to evolving data tools and business requirements
• Strong organizational skills and time management to handle multiple priorities
• 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) init

Benefits

Additional Information

Job Summary Synechron is seeking two experienced Data Engineers / Data Analysts to work within our Financial Data, Index & Analytics domain. These roles are pivotal in designing, developing, and maintaining enterprise-grade data solutions that support business analytics and decision-making processes. The successful candidates will leverage their technical expertise to build robust data models, optimize performance, and deliver insightful visualizations that drive business growth. These roles are essential for converting complex financial datasets into strategic intelligence, fostering data-driven decision-making across the organization. Software Requirements Required Skills: Advanced SQL (T-SQL), including CTEs, Window Functions, Dynamic SQL, and complex Joins Experience with SQL Server and Azure SQL for data transformation and warehousing projects Power BI Desktop & Power BI Service for creating dashboards, reports, and datasets Knowledge of data modeling techniques such as Star Schema and Snowflake Schema Experience with Azure Synapse Analytics, Databricks, and related data lake technologies Strong understanding of Data Warehousing methodologies, including slowly changing dimensions (SCD Type 1, 2, 3), aggregate tables, and fact tables Preferred Skills: Exposure to Microsoft Fabric and OneLake Python (Pandas, NumPy) for data processing and automation Experience with Azure Analysis Services and SSAS Tabular Models for enterprise semantic layers Overall Responsibilities Design, develop, and optimize enterprise data warehouse solutions and dimensional models aligned with business requirements Write complex T-SQL scripts, stored procedures, views, and functions for data transformation and reporting Implement indexing and query tuning strategies to optimize performance Build interactive dashboards and reports in Power BI, ensuring data accuracy and visual clarity Collaborate with cross-functional teams to gather requirements, translate them into technical solutions, and support ongoing data initiatives Maintain and enhance data pipelines and ETL processes, ensuring data integrity and high performance Support ad-hoc data analysis using Excel, Power Query, and Power Pivot for senior management Stay updated with emerging technologies and best practices in data warehousing, BI, and analytics Technical Skills (By Category) Programming Languages: Required: T-SQL, Power BI DAX, Power Query M language Preferred: Python (Pandas, NumPy) Databases & Data Management: SQL Server, Azure SQL, Data Warehouse modeling, SCD Types, Fact/Dimension tables Cloud Technologies: Azure Synapse Analytics, Azure Data Lake, Databricks (preferred) Frameworks & Libraries: Power BI, SSAS Tabular Models, Azure Analysis Services Development Tools & Methodologies: SQL Server Management Studio (SSMS), Visual Studio, Power BI Desktop, Agile/Scrum practices Security & Data Governance: Data privacy protocols, role-based access control, data validation Experience Requirements 5+ years of experience in data engineering, data analysis, or related fields Demonstrable experience in managing large-scale financial datasets and reporting Proven expertise in SQL development, data modeling for data warehouses, and BI report creation Experience working directly with business stakeholders to deliver analytics solutions Strong track record in performance tuning, indexing strategies, and ETL frameworks Day-to-Day Activities Design and develop scalable data models and APIs for financial data analysis Create and schedule Power BI dashboards and reports for various business units Optimize data pipelines, troubleshoot performance issues, and enhance data quality Engage with business users to gather requirements and deliver actionable insights Document configurations, processes, and best practices to support ongoing maintenance Review and improve data governance and security standards Collaborate with team members to support data migrations, upgrades, and new initiatives

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