The Role
Leads the design, development, and delivery of complex cloud-based data pipelines and scalable data systems. Translates business requirements into technical solutions, optimizes ingestion and transformation for performance and cost, and defines standards for data modeling, governance, reliability, and observability. Provides mentorship and technical leadership to data engineering teams while contributing to data architecture reviews and cross-functional technical decisions.
Summary Generated by Built In
Core Responsibilities:
Lead end-to-end design, development, and delivery of complex cloud-based data pipelines.
Collaborate with architects and stakeholders to translate business requirements into technical data solutions.
Ensure scalability, reliability, and performance of data systems across environments.
Provide mentorship and technical leadership to data engineering teams.
Define and enforce best practices for data modeling, transformation, and governance.
Optimize data ingestion and transformation frameworks for efficiency and cost management.
Contribute to data architecture design and review sessions across projects.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
8+ years of experience in data engineering with proven leadership in designing cloud-native data systems.
Strong expertise in Python, SQL, Apache Spark, and at least one cloud platform (Azure, AWS, or GCP).
Experience with Big Data, DataLake, DeltaLake, and Lakehouse architectures
Proficient in one or more database technologies (e.g. PostgreSQL, Redshift, Snowflake, and NoSQL databases).
Ability to recommend and implement scalable data pipelines
Preferred Qualifications:
Cloud certification (AWS, Azure, or GCP).
Experience with Databricks, Snowflake, or Terraform.
Familiarity with data governance, lineage, and observability tools.
Strong collaboration skills and ability to influence data-driven decisions across teams.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 8+ years of data engineering experience
- Proven leadership designing cloud-native data systems
- Strong expertise in Python
- Strong expertise in SQL
- Strong expertise in Apache Spark
- Experience with at least one cloud platform: Azure, AWS, or GCP
- Experience with Big Data, Data Lake, Delta Lake, and Lakehouse architectures
- Proficiency in one or more database technologies, including PostgreSQL, Redshift, Snowflake, or NoSQL databases
- Ability to recommend and implement scalable data pipelines
- Cloud certification in AWS, Azure, or GCP
- Experience with Databricks, Snowflake, or Terraform
- Familiarity with data governance, lineage, and observability tools
- Strong collaboration and ability to influence data-driven decisions across teams
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The Company
What We Do
Proclink is a digital and AI transformation company that helps regulated and operationally intensive enterprises modernize systems, workflows, and decision environments. It combines strategy and consulting, data engineering, artificial intelligence, analytics, implementation and integration, managed services, and technology services. The company serves manufacturing, financial services, life sciences, and other regulated industries, delivering connected enterprise intelligence and measurable operational performance for clients.
