Job Description
Self Motivated Engineer with a solid understanding of modern data ecosystems and a relentless drive for excellence and innovation. This role requires someone who thrives in dynamic environments, carrying strong technical foundations with adaptability and a product-focused mindset.
Key Responsibilities
- Design and deliver optimized, data-driven systems that address the Volume, Velocity, and Variety of enterprise-scale data.
- Develop, test, and maintain data pipelines and distributed data-processing workflows using Python, PySpark or equivalent processing engines.
- Integrate diverse data sources into unified, high-performing platforms that enable analytics and machine learning initiatives.
- Implement data orchestration using tools such as Airflow, within cloud ecosystems like AWS, Azure, or GCP.
- Apply best practices in data modeling, ETL/ELT design patterns, and schema evolution management.
- Emphasize clean code, modular architecture, and workflow automation for scalability and maintainability.
- Demonstrate agility in adopting new tools and methodologies, including GenAI technologies to enhance productivity and innovation in data workflows.
- Deliver end-to-end, product-grade data solutions focused on performance, reliability, and user impact.
- Maintain a proactive mindset with excellent communication, accountability, and execution discipline.
- Commit to continuous learning and innovation in data technologies and systems design.
Specialized Responsibilities
- Data Engineering & Modernization: Research and build reusable templates and frameworks for legacy-to-cloud migrations (e.g., Mainframe to Snowflake or Databricks).
- Governance & Metadata Management: Develop automated frameworks for data cataloging, metadata enrichment, and AI-ready data quality gates to ensure trusted, compliant datasets.
- Data Platforms & Consumption: Craft advanced BI accelerators and real-time semantic layers to empower analytics, reporting, and executive decision-making across the enterprise.
Experience Required
- 2–5 years of hands-on experience in data engineering or equivalent technical roles.
- Proven ability to build, optimize, and deploy data systems in production across distributed environments.
What We Offer:
NucleusTeq culture - Our positive and supportive culture encourages our associates to do their best work every day. We celebrate individuals by recognizing their uniqueness and offering them the flexibility to make daily choices that can help them to be healthy, centered, confident, and aware. We offer well-being programs and are continuously looking for new ways to maintain a culture where our people excel and lead healthy, happy lives.
We bring to the table:
Competitive salary and benefits package.
Hybrid work Model.
Opportunity to work with cutting-edge technologies.
Collaborative and inclusive work environment.
Professional development and growth opportunities.
