Job Description

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