The Role
Leads the design, development, and optimization of large-scale cloud data pipelines and ETL/ELT systems. Builds infrastructure for collecting, transforming, and distributing customer data while ensuring quality, security, scalability, and performance. Collaborates with architects, analysts, and stakeholders, mentors engineers, researches new tools, and supports DevOps through CI/CD and infrastructure-as-code practices.
Summary Generated by Built In
Core Responsibilities:
Lead the design and optimization of large-scale, cloud-based data pipelines and systems.
Develop infrastructure to collect, transform, combine, and publish/distribute customer data
Mentor junior engineers and contribute to best practices for data engineering standards.
Collaborate closely with data architects, analysts, and stakeholders to deliver reliable data solutions.
Implement and optimize ETL/ELT processes for performance and scalability.
Ensure data quality, integrity, and security across all environments.
Research and implement new tools, frameworks, and automation strategies to enhance productivity.
Support DevOps initiatives through CI/CD pipeline management and infrastructure-as-code practices.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
4.5+ years’ experience as a data engineer or relevant role
Understanding of Big Data technologies, DataLake, DeltaLake, Lakehouse architectures
Advanced proficiency in Python, SQL, and Apache Spark.
Deep understanding of data modeling, ETL/ELT processes, and data warehousing concepts.
Experience with cloud data platforms such as Azure Data Factory, AWS Glue, or GCP Dataflow.
Strong background in performance tuning and handling large-scale datasets.
Familiarity with version control, CI/CD pipelines, and agile development practices.
Proficient with handling different file formats: JSON, Avro, and Parquet
Knowledge of one or more database technologies (e.g. PostgreSQL, Redshift, Snowflake, NoSQL databases).
Preferred Qualifications:
Cloud certification from a major provider (AWS, Azure, or GCP).
Hands-on experience with Snowflake, Databricks, Apache Airflow, or Terraform.
Exposure to data governance, observability, and cost optimization frameworks.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 4.5 or more years of experience as a data engineer or in a relevant role
- Understanding of Big Data technologies, Data Lake, Delta Lake, and Lakehouse architectures
- Advanced proficiency in Python, SQL, and Apache Spark
- Strong understanding of data modeling, ETL/ELT processes, and data warehousing
- Experience with cloud data platforms such as Azure Data Factory, AWS Glue, or GCP Dataflow
- Experience with performance tuning and large-scale datasets
- Familiarity with version control, CI/CD pipelines, and agile development
- Proficiency handling JSON, Avro, and Parquet file formats
- Knowledge of database technologies such as PostgreSQL, Redshift, Snowflake, or NoSQL databases
- Cloud certification from AWS, Azure, or GCP
- Hands-on experience with Snowflake, Databricks, Apache Airflow, or Terraform
- Exposure to data governance, observability, and cost optimization frameworks
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
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.
