Data Engineering Team Lead
📝 Opis główny / Wstęp
Overview
We are a leader in AI-powered business operations, providing digital solutions and consulting services that help companies improve and grow. We focus on using advanced technology to make operations more efficient and find new ways to create value, especially in private capital markets.
Our system includes three main parts:
PaaS (Platform as a Service): An AI-based platform to improve workflows, generate insights, and speed up value creation.
SaaS (Software as a Service): A cloud platform that offers high performance, intelligence, and scalable solutions.
S&C (Solutions and Consulting): Modular tools and guides to help companies manage, grow, and optimize performance.
With over ten years of experience working with fast-growing companies and private equity-backed platforms, we have strong expertise and a track record of turning technology into a strategic advantage.
The Opportunity
We are looking for a Senior Data Architect with strong skills in cloud data architecture, data modeling, SQL, and data governance for large-scale systems.
Responsibilities
Create and maintain enterprise data strategies, standards, and designs to support operations, analytics, and AI/ML workloads.
Build cloud-based data solutions on platforms like AWS (Redshift, RDS, Glue, Lake Formation) or similar, ensuring they are scalable, secure, and cost-effective.
Define and enforce data modeling standards (dimensional models, denormalized schemas, OLTP/OLAP designs).
Manage data transformation using DBT, ensuring models are modular, tested, and documented.
Lead design of data integration using Prefect or Airflow, including batch, real-time, event-driven, and API-based processes.
Implement data quality, validation, and testing to ensure accurate and consistent data.
Set up data governance for quality, lineage, cataloging, classification, and access control.
Work with engineers and analytics teams to turn business needs into scalable data designs.
Recommend data tools, technologies, and platforms, and guide technical decisions.
Optimize data storage, indexing, and performance for large datasets.
Document data contracts, schemas, and interfaces across teams.
Ensure data architectures support AI/ML, including feature stores and model datasets.
Review architecture and code to meet standards and maintainability.
Cleanse and validate data, handling errors carefully.
Mentor data engineers on best practices.
Support automated deployment and CI/CD for data infrastructure.
Requirements
Experience managing and mentoring a team.
7+ years in data architecture, data engineering, or related roles.
5+ years building cloud-based data architectures (AWS, GCP, or Azure).
5+ years writing complex SQL queries.
5+ years creating ETL/ELT pipelines with Airflow, Prefect, or similar tools.
Experience with DBT for transformations, testing, and documentation.
Knowledge of data warehouse design (OLTP, OLAP, star/snowflake schemas).
Experience with data modeling tools and methodologies.
Experience with cloud data warehouses like Redshift, Snowflake, or BigQuery.
Familiarity with data governance, quality frameworks, and metadata management.
Understanding of AI/ML data needs, including feature stores and vector retrieval.
Bachelor’s degree in Computer Science or similar (preferred).
Pluses (optional skills): Python (Pandas, PySpark), Docker, Kubernetes, CI/CD, AWS Lambdas/Step Functions, Databricks, vector databases, data mesh/fabric, graph databases, cloud certifications.
Why Join Us?
We value people who solve problems creatively, learn quickly, work well in diverse teams, and aim high. We work hard but also make sure to have fun along the way.