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AI Summary
Company Description
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
Job Description
- 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
Qualifications
- 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
WILL BE A PLUS
- 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
Additional Information
PERSONAL PROFILE
- Proactive and ownership-driven mindset with a focus on long-term platform sustainability
- Strong analytical and problem-solving skills with attention to detail and data quality
- Ability to communicate complex technical concepts in a clear and structured way
- Collaborative team player comfortable working with cross-functional stakeholders
- Continuous learner interested in modern data engineering practices and AI-assisted development
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