3Core Systems
Contract | 3Core Systems, Inc | United States
Location: Plantation, FL (Hybrid – 4 Days a week onsite)
Duration:لیل 6 Months Contract to Hire
Job Description
Administer, optimize, and scale our Databricks Lakehouse environment, ensuring high performance, cost efficiency, and operational excellence.
Develop, maintain, and enhance our data platform infrastructure and security configurations using
Terraform
to provision Databricks workspaces, SQL Endpoints, Unity Catalog objects, and network components.
Manage and enforce
Unity Catalog
for data __________ governance, access control, and metadata management.
Implement and manage
CI/CD pipelines
for data pipelines, dbt projects, and infrastructure deployments using
GitHub Actions .
Automate operational tasks, monitoring, and alerting for the data platform.
Implement and enforce DevSecOps principles, working closely with security teams to ensure compliance and manage/rotate credentials securely.
Design and implement data ingestion patterns into Databricks using
Delta Lake, optimizing
for large-scale data processing and storage.
Develop, optimize, and troubleshoot complex
Spark jobs (PySpark/Scala)
for data processing and transformation within Databricks.
Manage and extend data ingestion pipelines using
Airbyte
(or similar modern tools like Fivetran, Stitch), including configuring connectors, monitoring syncs, and ensuring data quality and reliability from diverse source systems ( elektron ERP, CRM, marketing, supply chain).
Orchestrate and automate data pipelines and dbt models using Databricks Workflows and potentially integrating with other orchestration tools.
Collaborate with Analytics Engineers to translate business requirements into efficient and scalable data models using
dbt
(Data Build Tool).
Implement dbt best practices for modularity, testing, documentation, and version control, ensuring seamless integration with Databricks.
Partner effectively with Analytics Engineers, Data Scientists, and business stakeholders to deliver high-quality data solutions.
Provide technical guidance and mentorship to junior team members, and champion data engineering best practices, code quality, and documentation standards.
Qualifications & Skills
Education:
Bachelor's degree in Computer Science, Data Engineering, or a related technical field required.
Experience:
5+ years of progressive experience as a Data Engineer, with a strong focus on cloud-based data platforms.
Deep Databricks Expertise:
Extensive experience with Spark (PySpark/Scala), Delta Lake, Unity Catalog, Databricks SQL, and platform administration.
Data Modeling:
Proven experience with
dbt
for data modeling, transformation, and testing.
Infrastructure as Code (IaC):
Strong proficiency with
Terraform
for defining, provisioning, and managing cloud infrastructure and Databricks resources as code.
DevOps & CI/CD:
Expertise in Git and
GitHub Actions
for version control and implementing robust CI/CD pipelines.
Programming:
Proficiency in
SQL
and at least one programming language (Python strongly preferred, Scala is a plus).
Data Architecture:
Solid understanding of data warehousing, data lake, and lakehouse architectures.
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Location: Plantation, FL (Hybrid – 4 Days a week onsite)
Duration:لیل 6 Months Contract to Hire
Job Description
Administer, optimize, and scale our Databricks Lakehouse environment, ensuring high performance, cost efficiency, and operational excellence.
Develop, maintain, and enhance our data platform infrastructure and security configurations using
Terraform
to provision Databricks workspaces, SQL Endpoints, Unity Catalog objects, and network components.
Manage and enforce
Unity Catalog
for data __________ governance, access control, and metadata management.
Implement and manage
CI/CD pipelines
for data pipelines, dbt projects, and infrastructure deployments using
GitHub Actions .
Automate operational tasks, monitoring, and alerting for the data platform.
Implement and enforce DevSecOps principles, working closely with security teams to ensure compliance and manage/rotate credentials securely.
Design and implement data ingestion patterns into Databricks using
Delta Lake, optimizing
for large-scale data processing and storage.
Develop, optimize, and troubleshoot complex
Spark jobs (PySpark/Scala)
for data processing and transformation within Databricks.
Manage and extend data ingestion pipelines using
Airbyte
(or similar modern tools like Fivetran, Stitch), including configuring connectors, monitoring syncs, and ensuring data quality and reliability from diverse source systems ( elektron ERP, CRM, marketing, supply chain).
Orchestrate and automate data pipelines and dbt models using Databricks Workflows and potentially integrating with other orchestration tools.
Collaborate with Analytics Engineers to translate business requirements into efficient and scalable data models using
dbt
(Data Build Tool).
Implement dbt best practices for modularity, testing, documentation, and version control, ensuring seamless integration with Databricks.
Partner effectively with Analytics Engineers, Data Scientists, and business stakeholders to deliver high-quality data solutions.
Provide technical guidance and mentorship to junior team members, and champion data engineering best practices, code quality, and documentation standards.
Qualifications & Skills
Education:
Bachelor's degree in Computer Science, Data Engineering, or a related technical field required.
Experience:
5+ years of progressive experience as a Data Engineer, with a strong focus on cloud-based data platforms.
Deep Databricks Expertise:
Extensive experience with Spark (PySpark/Scala), Delta Lake, Unity Catalog, Databricks SQL, and platform administration.
Data Modeling:
Proven experience with
dbt
for data modeling, transformation, and testing.
Infrastructure as Code (IaC):
Strong proficiency with
Terraform
for defining, provisioning, and managing cloud infrastructure and Databricks resources as code.
DevOps & CI/CD:
Expertise in Git and
GitHub Actions
for version control and implementing robust CI/CD pipelines.
Programming:
Proficiency in
SQL
and at least one programming language (Python strongly preferred, Scala is a plus).
Data Architecture:
Solid understanding of data warehousing, data lake, and lakehouse architectures.
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