Team Lead Data Engineering at RemoDevs (вакансія неактивна)

ABOUT THE PROJECT

We are a company specializing in AI-powered enterprise operations, delivering digital solutions and consulting services that drive value and transform businesses. The focus is on leveraging advanced technology to streamline operations, improve efficiency, and unlock new revenue opportunities, particularly within private capital markets. The ecosystem includes an AI-native PaaS platform designed to optimize workflows and surface insights, a high-performance SaaS cloud solution for scalable execution, and modular technology playbooks supporting business growth and optimization. With over a decade of experience supporting high-growth and private equity-backed companies, the organization turns technology into a strategic advantage.

REQUIREMENTS

– 7+ years in data engineering or data architecture roles.
– 5+ years designing cloud-based architectures (AWS, GCP, or Azure).
– Strong experience writing complex SQL and building ETL/ELT pipelines using tools such as Airflow or Prefect.
– Hands-on experience with DBT for transformation and documentation.
– Expertise in data warehouse design (OLTP, OLAP, star/snowflake schemas) and modeling methodologies.
– Strong understanding of data governance, metadata management, and quality frameworks.
– Proven experience managing and mentoring teams.
– Bachelor’s degree in Computer Science or a related field (preferred).

RESPONSIBILITIES

– Design and maintain enterprise data architecture strategies and blueprints.
– Build cloud-native solutions on AWS (Redshift, RDS, Glue, Lake Formation) or equivalent platforms.
– Define and enforce standards for dimensional modeling, denormalized schemas, OLTP/OLAP patterns, and AI-ready data structures.
– Design data transformation layers using DBT and oversee orchestration with tools like Airflow or Prefect across batch, streaming, and event-driven pipelines.
– Establish data validation, quality control, and testing frameworks.
– Maintain governance practices for lineage, cataloging, and access control.
– Ensure data platforms support downstream AI/ML use cases, including feature stores, embeddings, and training datasets.
– Lead, mentor, and develop team members. Drive technical decisions and conduct architecture and code reviews.

WHAT WE OFFER

We value creative problem solvers who learn quickly, thrive in a diverse and open environment, and continuously push for higher standards. The team is focused on delivering high-quality solutions while maintaining a positive and engaging work culture.

COMPENSATION & BENEFITS

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