Brooksource
Data Engineer
Contract-to-Hire (6 months)
Lancaster, PA
We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and data infrastructure that support analytics, AI, and data-driven decision-making. This role is hands-on and focused on building reliable, well-modeled datasets across modern cloud and lakehouse platforms. You will partner closely with analytics, data science, and business teams to deliver high-quality data solutions.
Key Responsibilities Design, build, and optimize
batch and real-time data pipelines
for ingestion, transformation, and delivery Develop and maintain
data models
that support analytics, reporting, and machine learning use cases Design scalable
data architecture
integrating structured, semi-structured, and unstructured data sources Build and support
ETL / ELT workflows
using modern tools (e.g., dbt, Airflow, Databricks, Glue) Ingest and integrate data from multiple internal and external sources, including APIs, databases, and cloud services Manage and optimize
cloud-based data platforms
(AWS, Azure, or GCP), including lakehouse technologies such as Snowflake or Databricks Implement
data quality, validation, governance, lineage, and monitoring
processes Support advanced analytics and
machine learning data pipelines Partner with analysts, data scientists, and stakeholders to deliver trusted, well-structured datasets Continuously improve data workflows for
performance, scalability, and cost efficiency Contribute to documentation, standards, and best practices across the data engineering function
Required Qualifications 37 years of experience in
data engineering
or a related role Strong proficiency in
SQL
and at least one programming language (Python, Scala, or Java) Hands-on experience with
modern data platforms
(Snowflake, Databricks, or similar) Experience building and orchestrating
data pipelines
in cloud environments Working knowledge of
cloud services
(AWS, Azure, or GCP) Experience with
version control, CI/CD , and modern development practices Strong analytical, problem-solving, and communication skills Ability to work effectively in a fast-paced, collaborative environment
Preferred / Nice-to-Have Experience with
dbt, Airflow, or similar orchestration tools Exposure to
machine learning or advanced analytics pipelines Experience implementing
data governance or quality frameworks Familiarity with
SAP data platforms
(e.g., BW, Datasphere, Business Data Cloud) Experience using
LLMs or AI-assisted tooling
for automation, documentation, or data workflows Relevant certifications in cloud, data platforms, or AI technologies
We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and data infrastructure that support analytics, AI, and data-driven decision-making. This role is hands-on and focused on building reliable, well-modeled datasets across modern cloud and lakehouse platforms. You will partner closely with analytics, data science, and business teams to deliver high-quality data solutions.
Key Responsibilities Design, build, and optimize
batch and real-time data pipelines
for ingestion, transformation, and delivery Develop and maintain
data models
that support analytics, reporting, and machine learning use cases Design scalable
data architecture
integrating structured, semi-structured, and unstructured data sources Build and support
ETL / ELT workflows
using modern tools (e.g., dbt, Airflow, Databricks, Glue) Ingest and integrate data from multiple internal and external sources, including APIs, databases, and cloud services Manage and optimize
cloud-based data platforms
(AWS, Azure, or GCP), including lakehouse technologies such as Snowflake or Databricks Implement
data quality, validation, governance, lineage, and monitoring
processes Support advanced analytics and
machine learning data pipelines Partner with analysts, data scientists, and stakeholders to deliver trusted, well-structured datasets Continuously improve data workflows for
performance, scalability, and cost efficiency Contribute to documentation, standards, and best practices across the data engineering function
Required Qualifications 37 years of experience in
data engineering
or a related role Strong proficiency in
SQL
and at least one programming language (Python, Scala, or Java) Hands-on experience with
modern data platforms
(Snowflake, Databricks, or similar) Experience building and orchestrating
data pipelines
in cloud environments Working knowledge of
cloud services
(AWS, Azure, or GCP) Experience with
version control, CI/CD , and modern development practices Strong analytical, problem-solving, and communication skills Ability to work effectively in a fast-paced, collaborative environment
Preferred / Nice-to-Have Experience with
dbt, Airflow, or similar orchestration tools Exposure to
machine learning or advanced analytics pipelines Experience implementing
data governance or quality frameworks Familiarity with
SAP data platforms
(e.g., BW, Datasphere, Business Data Cloud) Experience using
LLMs or AI-assisted tooling
for automation, documentation, or data workflows Relevant certifications in cloud, data platforms, or AI technologies