Databricks Data Platform Architect (Sales Lakehouse)

Ethereum Technologies; Harrisburg (Dauphin County); On-site; USD 85,000 - 121,000; Part time

Job summary

Ethereum Technologies in Harrisburg, PA seeks an experienced Databricks Data Engineer to design and implement a scalable Sales Data Platform on Databricks (AWS). The role is hands-on and architecture-driven, focusing on ingestion, transformation, modelling, and optimization using modern Lakehouse patterns.

You will define end-to-end Lakehouse architecture, establish data modelling standards for Sales domains, and drive performance, scalability, and cost optimisation for large-scale pipelines.

Qualifications

• 8+ years in Data Engineering / Data Architecture roles.
• 4+ years hands-on experience with Databricks.
• Strong expertise in PySpark & Spark SQL.
• Deep experience with Delta Lake.
• Strong knowledge of AWS cloud services (S3, IAM, Glue, CloudWatch).
• Strong understanding of: Fact & dimension modelling; Slowly Changing Dimensions (SCD Type 1 / 2); Large-scale data processing patterns.
• Experience handling high-volume, high-velocity datasets.

Responsibilities

• Lead design and implementation of a scalable Sales Data Platform on Databricks (AWS).
• Hands-on role focused on data ingestion, transformation, modelling, and optimization using Lakehouse patterns.
• Define end-to-end Lakehouse architecture on Databricks (AWS) for Sales data domains.
• Establish data modelling standards for Sales facts, dimensions, hierarchies, and aggregations.
• Drive performance, scalability, and cost optimisation for pipelines.
• Build PySpark-based data pipelines in Databricks and ensure fault-tolerance.

Skills

8+ years data engineering

4+ years Databricks hands-on

PySpark & Spark SQL

Delta Lake

AWS services (S3, IAM, Glue, Cloud1, 0

Tools

Databricks

PySpark

Spark SQL

Delta Lake

AWS Glue

Amazon S3

CloudWatch

IAM

Job description

Ethereum Technologies in Harrisburg, PA seeks an experienced Databricks Data Engineer to design and implement a scalable Sales Data Platform on Databricks (AWS). The role is hands-on and architecture-driven, focusing on ingestion, transformation, modelling, and optimization using modern Lakehouse patterns.

You will define end-to-end Lakehouse architecture, establish data modelling standards for Sales domains, and drive performance, scalability, and cost optimisation for large-scale pipelines.