Hybrid Analytics Engineer: Data Lakehouse & AI Enablement

Baker Botts LLP; Austin, Northern (TX, KY); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work arrangement

Job summary

Baker Botts L.L.P. in Austin seeks an Analytics Engineer to transform enterprise data into trusted analytics-ready assets supporting reporting, BI, and AI initiatives across the firm.

You will design and maintain data transformations in Azure Databricks, own Bronze-to-Silver/Gold pipelines, ensure data quality, and deliver curated datasets for dashboards and self-service analytics. The role blends engineering with stakeholder engagement and requires strong Python, PySpark, and cloud data

Qualifications

• 5-7 years in analytics engineering or similar field.
• Strong Python skills for data transformation and validation.
• Hands-on Azure Databricks experience with Delta Lake.
• Experience with PySpark and large-scale datasets.
• BI tool experience (Power BI/Tableau).
• Knowledge of data quality, governance, and lineage.

Responsibilities

• Partner with stakeholders to translate requirements into data solutions.
• Define business rules, transformation logic, data lineage, and quality checks.
• Develop Bronze-to-Silver/Gold pipelines for trusted datasets.
• Maintain reusable metrics and analytics data products.
• Build PySpark workflows and Delta Lake assets.
• Support dashboards and analytics with clean data.

Skills

Python

PySpark

Azure Databricks

Delta Lake

Power BI

Tableau

Data quality

Data governance

Cloud data platforms

Data modeling

Tools

Azure Databricks

Delta Lake

Unity Catalog

Job description

Baker Botts L.L.P. in Austin seeks an Analytics Engineer to transform enterprise data into trusted analytics-ready assets supporting reporting, BI, and AI initiatives across the firm.

You will design and maintain data transformations in Azure Databricks, own Bronze-to-Silver/Gold pipelines, ensure data quality, and deliver curated datasets for dashboards and self-service analytics. The role blends engineering with stakeholder engagement and requires strong Python, PySpark, and cloud data