About the Company
Analyttica is a rapidly growing leader in data and analytics, driven by a passion for solving complex challenges and delivering high-impact projects. We specialize in tackling transformative initiatives that shape the future of data-driven business, blending the art and science of data to create lasting value.
About the Role
We are seeking a talented Data Engineer with hands-on experience in Python, DBT, and Machine Learning. You will design, develop, and optimize end-to-end data pipelines to process and transform raw data, collaborating closely with data scientists and product teams to build scalable, production-ready ML solutions. Ensure data quality, reliability, and efficiency across workflows, and stay updated on modern data engineering tools, best practices, and ML workflow optimizations to drive impactful analytics and ML initiatives.
Responsibilities
- Build end-to-end data pipelines with Python, handling structured and unstructured data to power analytics and ML workflows.
- Develop DBT models and transformations that convert raw data into clean, production-ready datasets for downstream analytics and ML.
- Collaborate with data scientists to integrate and operationalize ML models into scalable pipelines, ensuring reproducibility and performance.
- Monitor, optimize, and troubleshoot ETL workflows to maintain high-quality, reliable, and low-latency data delivery.
- Implement data validation, logging, and automated quality checks to ensure pipeline accuracy and consistency.
- Document data architecture, pipeline workflows, and ML integration strategies for transparency and maintainability.
- Stay ahead of modern tools, frameworks, and best practices in Python, DBT, and ML pipelines; propose improvements to the data roadmap.
Qualifications
- 35 years of experience in Data Engineering.
- Strong Python programming skills for ETL, data transformation, and workflow automation.
- Hands-on experience with DBT for data modeling, transformations, and pipeline management.
- Exposure to Machine Learning workflows, including integrating ML models and preparing ML-ready datasets.
- Proficiency in SQL and experience working with relational databases (PostgreSQL, MySQL, etc.).
- Strong analytical and problem-solving skills, with the ability to work independently in a fast-paced environment.
- Passion for staying updated with modern data engineering tools, best practices, and ML workflows.
