Senior Data Engineer

Sigma Software

1d•Remote

About The Position

Join our internal data-driven initiative as a Senior Data Engineer and help shape Sigma Software’s corporate Data Platform that powers analytics and decision-making across the company. This is a Senior-level role with a strong focus on data architecture, ELT, and self-service analytics. You will work in a primarily remote setup with close collaboration across distributed teams, partnering with BI Engineers, Business Analysts, and business stakeholders. We at Sigma Software are building a scalable, reliable, and secure data foundation to support reporting, analytics, and operational insights company-wide. In this role, you will influence platform evolution, introduce modern data engineering practices, and mentor other engineers. You will also benefit from a culture that supports professional growth, knowledge sharing, and the use of modern tools, including AI-assisted engineering, to deliver high-quality solutions efficiently. CUSTOMER This is an internal Sigma Software initiative. You will work directly with Sigma Software’s business units and internal stakeholders, helping them leverage data to improve operational efficiency, reporting, and strategic decision-making across the organization. PROJECT The project focuses on building and evolving Sigma Software’s corporate Data Platform (DPS) to improve data quality, automate reporting, and enable self-service analytics. You will design and enhance Data Warehouses and Data Marts, implement scalable ELT pipelines, and support analytical workloads that serve multiple business domains within the company. The platform is being developed with a strong emphasis on data governance, observability, and operational excellence. Key technologies: SQL, Python, ELT pipelines, orchestration tools (Dagster, Airflow or similar), analytical databases (e.g., ClickHouse), Apache Superset, BI and visualization tools

Requirements

5+ years of experience in Data Engineering with a proven track record of delivering complex data platform and analytics solutions
Strong expertise in SQL, Python, relational databases, and data modeling techniques for Data Warehouses and Data Marts
Hands-on experience designing and implementing enterprise-scale ELT pipelines and data processing solutions
Strong understanding of data architecture, data warehousing, dimensional modeling, and analytical data platforms
Experience with orchestration and workflow management tools such as Dagster, Airflow, or similar platforms
Strong knowledge of data governance, metadata management, data lineage, security, and access control models
Experience designing and optimizing analytical workloads, reporting systems, and self-service analytics platforms
Understanding of data quality management, monitoring, observability, and operational best practices for data platforms
Experience with analytical databases and performance optimization techniques (e.g., ClickHouse or similar technologies)
Strong knowledge of database fundamentals, including indexing, normalization, transactions, and query optimization
Hands-on experience in database development, data modeling, and analytical system design
Solid understanding of enterprise data architecture principles and modern data platform approaches
Strong AI-assisted engineering skills and practical experience using AI tools to improve development efficiency and solution quality
Strong communication skills and ability to collaborate effectively with technical and non-technical stakeholders
Intermediate English or higher

Nice To Haves

Experience with Apache Superset, Power BI, or other BI and visualization platforms
Experience with real-time or event-driven data processing solutions
Experience building internal data platforms and self-service analytics capabilities
Experience leading engineering teams or acting as a technical lead

Responsibilities

Design, build, and evolve Data Warehouses, Data Marts, and enterprise data models to support analytics and business decision-making
Design, implement, and optimize scalable ELT pipelines and data processing solutions, ensuring reliability, performance, and maintainability
Drive technical decisions related to data architecture, platform evolution, data modeling approaches, and integration patterns
Establish and maintain data governance practices, metadata standards, data lineage, security controls, and access management policies
Ensure data quality, observability, monitoring, and operational excellence across the data platform
Evaluate and introduce technologies, tools, and best practices that improve platform scalability, efficiency, and maintainability
Support and enhance self-service analytics capabilities through Apache Superset and other BI solutions
Collaborate closely with BI Engineers, Business Analysts, and business stakeholders to align data platform capabilities with organizational goals
Mentor Data Engineers, conduct technical reviews, and promote engineering best practices across the team
Apply AI-assisted engineering practices to improve development efficiency, delivery quality, and platform sustainability