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Data Engineer (Python)
Reads like an Analytics Engineer role: dbt models and clean tables.
Location not stated
Actively hiring, first seen by us 8 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingOwn and maintain the Dataform transformation layer for trusted reporting datasets
Build tested, documented transformation pipelines for business reporting
Run exploratory data analysis to find data quality issues and structure
Write performant BigQuery SQL with a focus on cost and speed
Add data quality and validation checks inside the transformation process
From the employer’s posting
own the transformation and modeling layers of a new data warehouse project
Build and manage scalable, well-documented, and tested data transformation pipelines
Conduct Exploratory Data Analysis (EDA) on new and existing datasets
Write highly performant BigQuery SQL for complex queries, aggregations, and data manipulation
Implement rigorous data quality and validation checks within the transformation process
What you’ll bring
All qualificationsCore experience
- 4 years of experience
- In-depth experience designing dimensional warehouses using Kimball principles
- Mastery of Dataform for production SQL transformation workflows
- Advanced SQL, including window functions, CTEs, and complex joins
- Deep BigQuery experience: performance tuning, cost optimization, partitioning and clustering
Qualification wording
Years of Experience Needed 4
Demonstrable, in-depth experience designing and building dimensional data warehouses using Kimball's principles.
Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment.
Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins.
Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering.
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 20268 days ago
- Recorded sightings
- 9
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Zylun Philippines is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- BigQuery
- Looker
- Power BI
- Tableau
Where the posting names them
Required Skills Google BigQuery (2), Python (4), Gemini Enterprise (1), Artificial Intelligence (AI) (1) Years of Experience Needed 4
- Build and manage scalable, well-documented, and tested data transformation pipelines that are critical for business reporting. - Conduct Exploratory Data Analysis (EDA) on new and existing datasets to identify quality issues, understand data structures, and unlock business value.Write highly performant BigQuery SQL for complex queries, aggregations, and data manipulation, with a focus on cost and speed optimization. - Implement rigorous data quality and validation checks within the transformation process to ensure accuracy and trust in our reporting datasets.
- Kimball Methodology: Demonstrable, in-depth experience designing and building dimensional data warehouses using Kimball's principles. - Dataform Expertise: Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment. - Expert-Level SQL: Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins.
- Dataform Expertise: Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment. - Expert-Level SQL: Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins. - Google BigQuery: Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering.
- BigQuery ML (BQML): Experience with building and deploying machine learning models using BQML is a significant plus. - Version Control (Git): Proficiency in using Git for managing SQL and Dataform code. Required Skills
Overview We are seeking a highly skilled Data Engineer to own the transformation and modeling layers of a new data warehouse project. This role is centered around an expert-level mastery of Google BigQuery (including Dataform). You will be responsible for taking raw data and architecting clean, reliable, and performant data models by applying Kimball methodology principles to power business intelligence and analytics. Your expertise in building sophisticated, scalable transformation pipelines with Dataform will be vital in transforming complex datasets into actionable insights and ensuring the analytical integrity of our dimensional data warehouse. Responsibilities
- Expert-Level SQL: Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins. - Google BigQuery: Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering. - Database Schema Concepts: Strong, practical knowledge of data warehousing schemas (Star Schema, Snowflake Schema, Data Marts).
- Business Intelligence (BI) Tool Integration: Experience preparing data for consumption by BI tools like Looker, Tableau, or Power BI. - BigQuery ML (BQML): Experience with building and deploying machine learning models using BQML is a significant plus. - Version Control (Git): Proficiency in using Git for managing SQL and Dataform code.
- Exploratory Data Analysis (EDA): Ability to analyze and profile datasets to derive insights and assess quality. - Business Intelligence (BI) Tool Integration: Experience preparing data for consumption by BI tools like Looker, Tableau, or Power BI. - BigQuery ML (BQML): Experience with building and deploying machine learning models using BQML is a significant plus.
Your next step
Complete your application on careers-codev.icims.com. The employer’s form will show what is required.
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- You start with your email. New applicants then create a login, and returning ones sign in.
- Upload your resume before you fill anything in: iCIMS fills some profile fields from it.
- Check your status on the employer’s iCIMS Dashboard, under Past Job Submittals.
Already applied? Track this application
About the role
We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Overview
We are seeking a highly skilled Data Engineer to own the transformation and modeling layers of a new data warehouse project. This role is centered around an expert-level mastery of Google BigQuery (including Dataform). You will be responsible for taking raw data and architecting clean, reliable, and performant data models by applying Kimball methodology principles to power business intelligence and analytics. Your expertise in building sophisticated, scalable transformation pipelines with Dataform will be vital in transforming complex datasets into actionable insights and ensuring the analytical integrity of our dimensional data warehouse.
Responsibilities
- Lead the development, maintenance, and optimization of the entire data transformation lifecycle using Dataform to produce high-quality, trusted datasets.
- Build and manage scalable, well-documented, and tested data transformation pipelines that are critical for business reporting.
- Conduct Exploratory Data Analysis (EDA) on new and existing datasets to identify quality issues, understand data structures, and unlock business value.Write highly performant BigQuery SQL for complex queries, aggregations, and data manipulation, with a focus on cost and speed optimization.
- Implement rigorous data quality and validation checks within the transformation process to ensure accuracy and trust in our reporting datasets.
Qualifications
- Kimball Methodology: Demonstrable, in-depth experience designing and building dimensional data warehouses using Kimball's principles.
- Dataform Expertise: Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment.
- Expert-Level SQL: Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins.
- Google BigQuery: Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering.
- Database Schema Concepts: Strong, practical knowledge of data warehousing schemas (Star Schema, Snowflake Schema, Data Marts).
- Exploratory Data Analysis (EDA): Ability to analyze and profile datasets to derive insights and assess quality.
- Business Intelligence (BI) Tool Integration: Experience preparing data for consumption by BI tools like Looker, Tableau, or Power BI.
- BigQuery ML (BQML): Experience with building and deploying machine learning models using BQML is a significant plus.
- Version Control (Git): Proficiency in using Git for managing SQL and Dataform code.
Required Skills
Google BigQuery (2), Python (4), Gemini Enterprise (1), Artificial Intelligence (AI) (1)Years of Experience Needed
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