Senior Data Analytics Engineer

Job Overview

We are seeking a Senior hands-on Data Analytics Engineer with strong expertise across Power BI, GCP, BigQuery, SQL, and data engineering. This role combines end-to-end analytics ownership with enterprise reporting and executive-level business intelligence.

The ideal candidate will have a proven track record of owning the full analytics lifecycle — from data ingestion, ETL/ELT, transformation, and data modeling in GCP to the development of scalable Power BI dashboards, semantic models, KPIs, and executive reporting.

This is not a traditional Power BI/reporting developer role. The successful candidate must have genuine, hands-on experience building and transforming data within GCP/BigQuery, developing data pipelines, and then leveraging that data to deliver enterprise-grade Power BI solutions.

The consultant will work closely with business stakeholders, data engineers, product owners, and senior leadership to translate business requirements into scalable, actionable analytics solutions.

Key Responsibilities

Design, develop, and maintain enterprise-grade Power BI dashboards, executive scorecards, KPI reporting, and operational analytics solutions.

Develop complex DAX measures, calculated columns, Power Query transformations, semantic models, and data models.

Design and implement scalable dimensional/star-schema data models for enterprise reporting.

Build and optimize GCP-based data ingestion, ETL/ELT, and data transformation pipelines.

Work extensively with Google BigQuery to develop, transform, optimize, and validate large-scale datasets.

Write complex and optimized SQL queries for data extraction, transformation, validation, and analysis.

Own data preparation and transformation processes rather than simply consuming pre-built datasets.

Perform data quality checks, reconciliation, validation, and troubleshooting across source systems and reporting layers.

Develop and maintain KPI frameworks and operational performance reporting.

Translate complex business requirements into scalable analytics, reporting, and visualization solutions.

Partner directly with business stakeholders and senior leadership to gather requirements, define KPIs, present insights, and drive data-informed decisions.

Optimize Power BI reports, semantic models, and BigQuery queries for performance and scalability.

Work with data engineering and product teams to ensure reliable, governed, and production-ready analytics solutions.

Support process analytics initiatives involving Statistical Process Control (SPC), process stability, thresholds, control charts, outlier/variance analysis, and operational health monitoring.

Required Qualifications

5+ years of hands-on Power BI development experience, including:

Power BI Desktop and Power BI Service

Advanced DAX

Power Query

Complex data modeling

Semantic models

Executive dashboards and scorecards

KPI and performance reporting

3+ years of hands-on Google Cloud Platform (GCP) experience.

Strong hands-on experience with Google BigQuery.

Strong SQL development and data transformation skills.

Proven experience developing ETL/ELT processes and data ingestion pipelines.

Experience building, transforming, and preparing data within GCP — not simply consuming datasets created by other teams.

Strong understanding of data modeling and dimensional modeling, including star-schema design.

Experience working with large-scale enterprise datasets.

Proven experience developing enterprise and executive-level dashboards, scorecards, and KPI frameworks.

Strong analytical and problem-solving skills.

Excellent communication and stakeholder management skills.

Ability to gather requirements and communicate complex data insights effectively to both technical and executive audiences.

Preferred Qualifications

Experience with Statistical Process Control (SPC) and control charts.

Experience supporting Human-in-the-Loop (HITL) or AI Operations analytics.

Lean, Six Sigma, or Continuous Improvement experience.

Hands-on Python experience.

Experience working with APIs and data integrations.

Experience with Git/source control.

Experience working in Agile/Scrum environments.

Knowledge of data governance, metadata management, and data quality frameworks.

Experience with process intelligence, workflow analytics, automation, observability, or operational monitoring.

Experience within financial services or other regulated industries.