Responsibilities

• Design and implement scalable data architectures and models to support analytics initiatives, ensuring data integrity, reliability, and accessibility.
• Data Extraction and Transformation: Develop ETL (Extract, Transform, Load) processes to collect, cleanse, and transform data from diverse sources, ensuring accuracy and efficiency.
• Analytics Solution Development: Build advanced analytics solutions and algorithms to analyze large datasets, uncover insights, and generate actionable recommendations for stakeholders.
• Visualization and Reporting: Create intuitive and interactive dashboards and reports to communicate key findings and trends, enabling stakeholders to make data-driven decisions effectively.
• Performance Optimization: Continuously optimize analytics processes and queries to improve efficiency, scalability, and reliability, ensuring timely delivery of insights.
• Collaboration and Communication: Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

Qualifications:

• Bachelor’s degree in computer science, mathematics, physics, statistics, or a related field with minimum 3 years of experience in data.
• Proficiency in programming languages such as Python, SQL, and R, with experience in data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Strong experience with data warehousing concepts and technologies (e.g., Bigquery, Snowflake, Redshift).
• Experience with cloud platforms (preferred): Experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure is increasingly valuable in analytics engineering roles.
• Experience with ETL/ELT tools and frameworks (e.g., Apache Spark, Airflow, Dagster) for data extraction, transformation, and loading.
• Expertise in data modeling for OLAP and star schema
• Hands-on experience with data visualization tools (e.g., Metabase, Looker) to create insightful dashboards and reports.
• Familiarity with machine learning concepts and algorithms is a plus.
• Analytical Mindset: Strong analytical and problem-solving skills, with the ability to translate complex business requirements into technical solutions.
• Communication Skills: Excellent written and verbal communication skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.