Job Description

About the Role

The Senior Analytics Engineer will be responsible for designing, developing, and maintaining end-to-end data solutions. This includes building robust data pipelines that extract data from source systems into a data warehouse, transforming raw data into well-modeled datasets for business intelligence, and creating interactive, user-friendly visualizations using Power BI.

The role requires close collaboration with cross-functional teams to enable stakeholders to derive actionable insights and make data-driven decisions.

Scope of Work and Responsibilities

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  Design and develop scalable data pipelines to extract and transform data from various source systems into the data warehouse.
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  Transform data into structured models following dimensional modeling techniques (e.g., Kimball).
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  Create visually compelling dashboards and reports using Power BI.
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  Collaborate with data analysts and stakeholders to understand requirements and deliver meaningful insights.
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  Ensure data accuracy and integrity through validation and quality checks.
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  Design intuitive and user-friendly visualizations tailored to stakeholder needs.
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  Participate in Agile development processes (Scrum, Kanban).
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  Prepare high-level and detailed technical designs for data solutions.
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  Apply best practices in coding, testing, and deployment, including CI/CD pipelines.
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  Stay updated with trends in data engineering and visualization; recommend improvements.
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  Perform other relevant tasks as assigned.

Qualifications and Requirements

Educational Requirements

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  Bachelor's degree in Information Technology, Engineering, Data Science, or a related field.

Experience and Skills

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  At least 5 years of experience in a senior analytics engineering or development role.
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  At least 5 years of experience in system architecture, design, and development of integrated solutions.
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  Strong analytical and problem-solving skills.
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  Strong understanding of dimensional modeling techniques.
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  Familiarity with software development lifecycle and project management methodologies.
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  Proven experience with relational databases (e.g., Oracle, SQL Server).
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  Proven experience building data pipelines using Python, PySpark, and SQL
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  Experience with Microsoft 365 tools.
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  Familiarity with cloud platforms such as Azure or AWS
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  Experience working in Agile environments (Scrum or Kanban).
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  Proficiency in Power BI; experience with Tableau or similar tools is a plus.

Preferred Qualifications

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  Experience building and maintaining ML or AI pipelines.
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  Exposure to Generative AI/LLM workflows, including chatbot integration and model orchestration.
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  Experience supporting ML solutions (e.g., predictive analytics, forecasting).
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  Experience with Azure DevOps.
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  Experience with cloud services and CI/CD pipelines.
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  Certifications in Secure Coding, Scrum, or DevOps are a plus.
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  Experience working in teams of five or more members.
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  Ability to work with senior stakeholders from diverse backgrounds.
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  Excellent oral and written communication skills in English.

Reporting and Deliverables

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  Reports to the Project Manager or designated supervisor.
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  Collaborates with business stakeholders, data analysts, and cross-functional teams.

Key Deliverables:

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  High-level and detailed technical designs
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  Secure, unit-tested code
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  Interactive and insightful dashboards

Work Arrangement

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  Hybrid setup, with onsite reporting at least three times per week (or as required).
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  Standard working hours: 8:00 AM – 5:00 PM (local time)