Data & Analytics - Technical Lead

Job description

**Must Have Technical/Functional Skills** Data Analytics, data Visualization tools, Python, SQL, **Roles & Responsibilities** **Position Overview** We are seeking a results-driven **Data & Analytics Specialist** to design, develop, and deliver data-driven insights that support strategic decision-making. The ideal candidate will have strong experience in **data analysis, visualization, and data engineering concepts**, along with proficiency in modern analytics tools and platforms. **Key Responsibilities** - Analyze large datasets to extract actionable insights and support business decisions - Design and develop **interactive dashboards and reports** using tools such as Power BI, Tableau, or similar - Build and maintain **ETL pipelines** for data integration and transformation - Collaborate with business stakeholders to gather requirements and translate them into analytical solutions - Perform **data modeling and data warehousing** activities - Ensure data quality, governance, and integrity across systems - Conduct exploratory data analysis and present findings with clear visualizations - Support advanced analytics initiatives such as **predictive modeling and machine learning (if applicable)** - Optimize queries and improve performance of data processes - Document processes, standards, and best practices **Required Skills & Qualifications** - Strong experience in **Data Analytics / Business Intelligence** - Proficiency in **SQL** and at least one programming language (Python, R, or similar) - Hands-on experience with **data visualization tools** (Power BI, Tableau, etc.) - Understanding of **data warehousing concepts** (Snowflake, Redshift, BigQuery, etc.) - Experience with **ETL tools** (Informatica, Talend, Azure Data Factory, etc.) - Knowledge of **data modeling techniques** - Strong analytical and problem-solving skills **Preferred Qualifications** - Experience with **cloud platforms** (Azure, AWS, or GCP) - Familiarity with **Big Data technologies** (Spark, Hadoop) - Exposure to **machine learning frameworks** - Experience in domain-specific analytics (Financial, Healthcare, Retail, etc.) - Certification in relevant tools (e.g., Power BI, AWS, Azure Data Engineer)