Senior Data Engineer
Nukasani Group
Location: Remote Position Overview
We are seeking a highly experienced and motivated Senior Data Engineer to support the design, development, optimization, and maintenance of enterprise-scale data infrastructure and data pipelines.
The Senior Data Engineer will leverage deep technical expertise and 10+ years of experience to develop scalable and reliable data solutions, support data engineering strategy, and ensure data is accessible, accurate, secure, and optimized across the organization.
The ideal candidate will have strong hands-on experience with data warehouses, data lakes, ETL/ELT pipelines, SQL, Python, cloud platforms, and modern data engineering technologies . This individual will also collaborate closely with technical teams and business stakeholders to translate requirements into high-quality data products.
Important: This is a contract position and is not a direct-hire opportunity with SMPA.
Key Responsibilities Data Pipeline Development- Design, develop, and maintain scalable, enterprise-grade data pipelines.
- Build complex, end-to-end ETL/ELT workflows that integrate data from multiple sources into data warehouses and data lakes.
- Develop reliable and reusable data transformation processes.
- Ensure data pipelines are scalable, maintainable, and production-ready.
- Contribute to the design and implementation of enterprise data infrastructure.
- Develop solutions that support high-volume data processing and analytics requirements.
- Translate business and technical requirements into effective data engineering solutions.
- Ensure data products align with the needs and objectives of data consumers.
- Establish and maintain high standards for data quality, integrity, and reliability.
- Implement appropriate data governance and security practices.
- Ensure data solutions comply with applicable organizational security and compliance requirements.
- Identify and address data quality issues across pipelines and platforms.
- Monitor, troubleshoot, and optimize data pipelines, databases, and data processing workflows.
- Improve data processing performance, scalability, reliability, and cost efficiency.
- Identify opportunities to optimize pipeline architecture and resource utilization.
- Work closely with data consumers, analysts, engineers, and other stakeholders to understand requirements and deliver effective solutions.
- Translate complex business requirements into scalable technical solutions.
- Provide technical guidance and mentorship to junior data engineers.
- Contribute to engineering standards, architecture decisions, and best practices.
- Develop and maintain comprehensive technical documentation.
- Document data architecture, transformation logic, pipeline processes, and technical standards.
- Promote and enforce coding, development, testing, and documentation best practices.
- 10+ years of professional Data Engineering experience , with hands-on experience working with:
- Data Warehouses
- Data Lakes
- ETL/ELT
- Data Pipelines
- Enterprise-scale data platforms
- Advanced proficiency in SQL and Python .
- Hands-on experience with at least one major cloud platform:
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure
- Strong experience with modern data warehouse technologies, including:
- Google BigQuery
- Amazon Redshift
- Experience with data pipeline orchestration and transformation technologies, including:
- Apache Airflow
- dbt (Data Build Tool)
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field .
- Must be based in the United States .
- Must be available to work within the Eastern or Central Time Zone .
- Fluent English communication skills.
- Strong analytical, troubleshooting, communication, and problem-solving abilities.
- 15+ years of Data Engineering experience .
- Master's degree in Computer Science, Information Systems, Engineering, or a related technical discipline.
- Proven experience optimizing large-scale data pipelines and data processing workloads.
- Previous experience within the pharmaceutical, life sciences, or healthcare industry .
- Experience with business intelligence and visualization platforms such as Tableau .
- Experience working with enterprise data products and supporting data consumers.
- Experience mentoring or providing technical guidance to other data engineers.
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