We are seeking highly technical Mid-Level or Senior Data Solutions Lead to design, build, and scale the organization’s data architecture and data modeling strategy. This role will be responsible for developing, maintaining, and optimizing the company’s data warehouse environment while ensuring data quality, scalability, and performance across the organization.
The ideal candidate combines strong technical expertise with a service-oriented mindset, capable of partnering closely with internal stakeholders to understand business needs, identify process improvement opportunities, and deliver practical, data-driven solutions.
Due to the cross-functional nature of the role, we are looking for someone with genuine curiosity and interest in understanding the operational processes and business objectives of multiple departments across the organization. The successful candidate must value the balance between technical excellence and real business impact.
Key Responsibilities
Lead the migration and modernization of the current Data Warehouse environment
Design, develop, and maintain the division’s Data Warehouse architecture
Collaborate with different business areas to analyze processes and ensure data quality standards
Connect, structure, and transform multiple data sources into scalable and standardized data models
Implement automated and monitored data ingestion pipelines, including alerting and error management processes
Create and maintain technical documentation to support future scalability and governance
Design scalable data structures and architectures that support long-term business growth
Support the evaluation and selection of technology tools related to data architecture and analytics
Ensure optimal performance, reliability, scalability, and integrity of the data environment
Develop and maintain multiple layers of the data ecosystem, including staging, transformation, and reporting layers
Preferred Profile
A collaborative team player with strong interpersonal skills
Personable and approachable when working with internal stakeholders
Customer service oriented, with a strong focus on supporting internal business needs
Techno-functional, with the ability to bridge technical solutions and business requirements effectively
Able to understand operational processes and translate business needs into scalable data solutions
Proactive, solution-driven, and adaptable in fast-paced environments
Able to communicate technical concepts clearly to non-technical audiences
Passionate about continuous improvement and data-driven decision-making
Required Skills
Strong communication and interpersonal skills
Analytical and critical thinking abilities
Technical leadership and problem-solving mindset
Process management and continuous improvement orientation
Resilience and adaptability in dynamic environments
Strong customer-service orientation focused on internal stakeholders
Experience & Qualifications
3–5 years of experience in Data Engineering, Analytics Engineering, or similar roles
Strong hands-on experience with dbt, including layered modeling, testing, macros, and documentation
Solid experience working within Microsoft Azure environments
Advanced SQL and Python skills (additional programming languages are considered a plus)
Experience with data ingestion and ETL/ELT tools
Preferred experience with technologies such as: Snowflake, BigQuery, Amazon Redshift, Airbyte, Fivetran, Similar cloud-based data platforms and ingestion tools
Technical Knowledge
Required: Azure SQL, Azure Synapse Analytics, Azure Data Factory (ADF), dbt, Advanced SQL & Python, Git / GitHub, Power BI or Metabase
Preferred: Snowflake, Airbyte
Language: English is a must
Systems & Access: SAP, Slack, Gmail, Corporate Domain, Microsoft Azure Environment
Equipment Provided: Company Laptop