Senior Analyst, Big Data Analytics & Engineering

Job Description

Role Responsibilities: Data Engineering & Pipeline Development: Develop and maintain robust data pipelines to support the value quantification process. Utilize tools such as Apache NiFi, Azure Data Factory, Pentaho, Talend, SSIS, and Alteryx to ensure efficient data integration and transformation. Data Management and Analysis: Manage and analyze large datasets using SQL, Hadoop, and other database management systems. Perform data extraction, transformation, and loading (ETL) to support value quantification efforts. Advanced Analytics Integration : Use advanced analytics techniques, including machine learning algorithms, to enhance data processing and generate actionable insights. Leverage programming languages such as Python (Pandas, NumPy, PySpark) and Impala for data analysis and model development. Business Intelligence and Reporting: Utilize business intelligence platforms such as Tableau and Power BI to create insightful dashboards and reports that communicate the value of services. Generate actionable insights from data to inform strategic decisions and provide clear, data-backed recommendations. Cross-Functional Collaboration & Stakeholder Engagement: Collaborate with Sales, Marketing, Consulting, Product, and other internal teams to understand business needs and ensure successful data solution development and deployment. Communicate insights and data value through compelling presentations and dashboards to senior leadership and internal teams, ensuring tool adoption and usage. All About You: Data Engineering Expertise: Proficiency in data engineering tools and techniques to develop and maintain data pipelines. Experience with data integration tools such as Apache NiFi, Azure Data Factory, Pentaho, Talend, SSIS, and Alteryx. Advanced SQL Skills: Strong skills in SQL for querying and managing large datasets. Experience with database management systems and data warehousing solutions. Programming Proficiency: Knowledge of programming languages such as Python (Pandas, NumPy, PySpark) and Impala for data analysis and model development. Business Intelligence and Reporting: Experience in creating insightful dashboards and reports using business intelligence platforms such as Tableau and Power BI. Statistical Analysis: Ability to perform statistical analysis to identify trends, correlations, and insights that support strategic decision-making. Cross-Functional Collaboration: Strong collaboration skills to work effectively with Sales, Marketing, Consulting, Product, and other internal teams to understand business needs and ensure successful data solution development and deployment. Communication and Presentation: Excellent communication skills to convey insights and data value through compelling presentations and dashboards to senior leadership and internal teams. Execution Focus: A results-driven mindset with the ability to balance strategic vision with tactical execution, ensuring that data solutions are delivered on time and create measurable business value. Education: Bachelor s degree in Data Science, Computer Science, Business Analytics, Economics, Finance, or a related field. Advanced degrees or certifications in analytics, data science, AI/ML, or an MBA are preferred.