Analytics Engineer Sr

The role

As an Analytics Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 3+ YEARS of experience, a growth mindset and a drive to make a lasting impact.

This BI and Analytics Engineer supports our client by delivering reliable data pipelines, reporting, and actionable insights. The role builds and maintains cloud-based ETL/ELT workflows using Databricks, APIs, and orchestration tools. It also develops automated reporting and Tableau dashboards, with Alteryx as a core skill.

Day to day work will alternate between long term (ETL and dashboard projects) and quick-turn analytics requests. Working largely independently, the engineer translates business questions into clear analyses defines and builds maintainable workflows for client stakeholders. The role safeguards delivery quality and timeliness, manages the backlog and provides attentive client service.

• A curious problem solver who challenges the status quo
• A collaborator who values teamwork and knowledge-sharing
• Excited by the intersection of technology, creativity and data
• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities

• Lead the development and maintenance of reusable, analysis-ready datasets for reporting, dashboarding, and analytical use cases.
• Translate business questions into structured analytical approaches, reporting requirements, data needs, and output designs with limited oversight.
• Analyze structured data to identify trends, anomalies, business drivers, and actionable opportunities.
• Own lightweight transformation logic and dashboard-ready data modeling needed to support accurate and scalable analytics outputs.
• Design and maintain ingest and business logic-based transformations in tools such as Alteryx, Databricks SQL, Pyspark and related cloud data environments.
• Build scalable ingestion pipelines using APIs and other connectors to ingest, transform and centralize data in analysis, data science and dashboard ready data sets.
• Build scalable analytical models that support Data Analysts, Data Scientists, AI Scientists, and business stakeholders with reliable and understandable data assets.
• Perform and improve data validation, QA, and logic review practices to ensure modeled datasets are accurate, complete, and aligned with business expectations.
• Troubleshoot moderately complex modeling, transformation, semantic, or metric consistency issues and work with adjacent teams to resolve them.
• Document transformation logic, source dependencies, joins, model assumptions, semantic definitions, and data quality considerations clearly and consistently.
• Support structured code review, version-controlled development, and reusable workflow practices for analytics engineering assets.
• Partner with Data Analysts, Data Scientists, AI Scientists, Data Engineers, and Architects to ensure transformed datasets align with reporting needs, modeling requirements, governed data structures, and platform realities.
• Improve delivery quality by identifying opportunities for better model structure, stronger metric consistency, cleaner documentation, and more scalable analytical workflows.
• Follow established governance, privacy, and data-quality standards in day-to-day work.

Must have qualifications

To be considered for this role, you must meet the following essential qualifications:

• A minimum of 3 years of hands-on experience in data engineering, cloud data platforms, and enterprise analytics solutions
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical field.
• Create dashboards in Power BI, Tableau, or similar BI tools.
• Develop Alteryx and other ETL for automated reporting.
• Translate complex analytical outputs into executive-friendly visualizations.
• Build, maintain, and support interactive reports with filters, drill-downs, and trend analysis.
• Ensure data quality and consistency behind dashboards and enabling business teams to understand reporting requirements and track numbers, rates, growth, correlation, etc.
• Databricks (Python, PySpark, SQL, Delta Lake, Workflows)
• Cloud data platforms and services (Azure /Databricks)
• API integrations and data ingestion frameworks
• ETL/ELT pipeline design, development, and support
• Workflow orchestration tools such as Airflow, Databricks Workflows, or Azure Data Factory
• Data modeling, performance optimization, monitoring, and operational support
• Power BI or enterprise BI platform development
• Data governance, security, access management, and production support
• Data validation and automated data anomaly detection
• Familiarity with Finance KPI and spatial data is a plus.

Collaboration / Stakeholder Expectations

• Serves as a dependable analytics engineering partner to internal teams and client stakeholders across transformation logic and reusable data asset needs.
• Works with Data Scientists and AI Scientists to ensure analytical and AI workflows are supported by reliable, governed, and appropriately modeled datasets.
• Participates confidently in client-facing discussions by explaining model logic, metric definitions, transformation choices, and data quality considerations in clear business language.
• Helps improve team consistency by strengthening documentation, sharing modeling best practices, and supporting more junior practitioners.

The benefits

Beyond a competitive compensation package, we offer:

• Flexibility, with remote and hybrid work options (country-dependent)
• Career advancement, with international mobility and professional development programs
• Learning and development, with access to cutting-edge tools, training and industry experts
• Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

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