Senior Data Analytics Engineer

Things to know before applying:

• you must have your own work equipment
• you are able to work remotely
• you can work full-time for this role
• currently residing in the Philippines
• only candidates who meet the requirements will be contacted

Role Summary

The Data Engineer will be part of the Data Analytics team, responsible for designing, building, and maintaining scalable data pipelines and infrastructure within a Microsoft Azure environment. This role requires a
balanced profile split equally between Data Engineering (50%) and Analytics Engineering (50%)

. You'll build robust data infrastructure whilst delivering actionable insights that drive business decisions, bridging technical implementation with business value. 

Key Responsibilities

Data Engineering (50%)

• Design, build, and maintain scalable data pipelines using Azure Data Factory, Fabric Dataflows, dbt, and Python/PySpark.
• Develop and optimise ETL/ELT processes handling incremental loads, CDC (Change Data Capture), SCD (Slowly Changing Dimensions), and late-arriving data.
• Design and implement data warehouse architectures (Star schema, Snowflake schema) and optimised Lakehouse structures.
• Build semantic models and optimised table structures supporting enterprise-scale analytics.
• Implement orchestration and automation solutions using Azure Functions and Logic Apps.
• Ensure data quality, integrity, and governance through robust testing frameworks and validation rules.
• Manage cloud infrastructure security, authentication, and access roles across Azure environments.

Analytics Engineering (50%)

• Translate business rules into scalable data models and reusable metrics layers.
• Develop and maintain Power BI reports and dashboards with advanced DAX calculations and enterprise-grade data modelling.
• Define and track key business metrics including churn, retention, cohorts, revenue/accrual calculations, and member lifetime value (LTV).
• Apply statistical analysis and predictive modelling concepts to support forecasting and behaviour modelling.
• Build data quality frameworks including dbt tests, validation rules, and lineage tracking.
• Deliver actionable insights through executive dashboards, operational dashboards, and financial reporting.
• Collaborate cross-functionally with finance, operations, marketing, and IT to gather requirements and translate them into technical solutions.
• Provide advisory input on reporting requirements, thinking like an engineer whilst delivering like an analyst.

Required Skills & Experience

1. Core Technical Skills (Data Engineering)

Data Modelling & Architecture

• Strong understanding of data warehouse design (Star schema, Snowflake schema)
• Experience designing semantic models and optimised table structures
• Ability to build scalable Lakehouse architectures

ETL/ELT Development

• Expert in building pipelines using:
• Azure Data Factory / Fabric Dataflows
• dbt
• Python / PySpark
• Handling incremental loads, CDC, SCD, late-arriving data

Cloud Technologies

• Experience with modern cloud platforms:
• Azure (SQL Database, Storage, Synapse, Fabric, Key Vault)
• AWS or GCP
• Strong understanding of security, authentication, access roles
• Orchestration & automation experience (Azure Functions, Logic Apps)

SQL Mastery

• Ability to write highly optimised SQL queries
• Understands indexing, query plans, partitioning
• Ability to debug performance issues in SQL

2. Analytics Engineering Skills

Business Logic Transformation

• Translating business rules into scalable data models
• Creating reusable metrics and semantic layers
• Handling complex joins, rollups, time series, revenue logic, churn, etc.

Data Quality & Governance

• Building frameworks for data testing (dbt tests, validation rules)
• Tracking lineage and defining documentation standards
• Ensuring data accuracy, completeness, and timeliness

Metrics & KPI Development

• Ability to define metrics such as:
• Churn, retention, cohorts
• Revenue/accrual calculations
• Member lifetime value (LTV)

Statistical Analysis & Behaviour Modelling

• Predictive Modelling Concepts
• Correlation & causation knowledge
• Descriptive statistics

3. Reporting, BI & Visualisation

Power BI Expertise

• Designing enterprise-grade dashboards
• Data modelling inside Power BI
• DAX calculations (advanced level)
• Building reusable datasets (Fabric)
• Performance optimisation

Visualisation Best Practices

• Understanding of user experience (UX)
• Ability to present insights clearly for:
• Executive dashboards
• Operational dashboards
• Financial reporting

4. Programming & Automation

Python

• ETL scripts, API extraction, cleaning, batch processes
• Automation for data validation and pipeline monitoring

API Integration

• Knowledge of REST APIs, authentication
• Pulling data from multiple SaaS platforms

Git

• Version control and collaboration

5. Data Strategy & Problem-Solving

Analytical Mindset

• Uses data to solve complex business challenges
• Ability to identify gaps in processes or systems
• Experience building:
• Forecasting models
• Membership behaviour analytics
• Churn prediction frameworks

Cross-functional Collaboration

• Works with finance, operations, marketing, and IT
• Gathers requirements and translates to technical solutions
• Communicates clearly with both technical and non-technical stakeholders

6. Soft Skills & Leadership Competencies

Communication

• Provides clear recommendations, not just data outputs

Ownership

• Takes accountability for quality and delivery
• Actively improves and documents processes

Adaptability

• Thrives in fast-moving environments
• Able to take projects from undefined → well-structured

Problem Ownership

• Thinks like an engineer but delivers like an analyst
• Proactive in identifying issues before they escalate

7. Nice-to-Have Skills

• Experience with Fabric end-to-end (OneLake, Pipelines, Warehouse)
• Experience in fitness industry, subscription billing, or membership lifecycle analytics
• ML basics: churn models, forecasting, clustering
• Exposure to tools like CI/CD
• Experience with cost optimisation in Cloud

Expectations

• Demonstrate strong business acumen and analytical capability, bridging technical and business domains effectively.
• Work independently with minimal supervision, taking ownership of project responsibilities and deliverables.
• Provide advisory capability on reporting requirements rather than simply taking instructions.
• Ensure transparency in progress and blockers.
• Adapt quickly to feedback and implement improvements effectively.
• Proven experience working in structured company environments.

Hiring Process:

• Phone screening
• Behavioral interview
• Technical Interview
• Client interview

About Adaca:

Adaca is at the forefront of bridging software development solutions by connecting Australian mid-tier companies with top-tier talents in the Philippines. Our unique approach is rooted in creating an employee-centric experience that fosters a simple, low-pressure environment for our developers. This philosophy not only enhances productivity but also delivers unparalleled value to our clients, fostering a cycle of growth and talent attraction.