About the Company
At Sourcing Trust, we are committed to delivering innovative, reliable, and tailored technology solutions that empower businesses to succeed in a rapidly evolving digital landscape. With a focus on excellence, integrity, and collaboration, we build lasting partnerships by understanding our clients' unique needs and providing them with expert support across. Our team is dedicated to fostering a positive and inclusive work environment where every employee's contribution is valued, encouraging continuous growth, learning, and shared success. Join us and be part of a passionate organization driven by innovation and excellence.
About the Role
We are seeking motivated and skilled Senior Analytics Engineers and Mid Analytics Engineers to lead the design, implementation, and optimization of advanced analytical solutions. This role requires strong technical expertise, strategic thinking, and the ability to align data architecture with business goals while supporting cross-functional teams.
Requirements
Responsibilities
Model and transform data into consistent analytical structures.
Build and optimize ELT pipelines and quality tests.
Ensure clear documentation (business rules, lineage, transformation logic).
Monitor datasets, quality, SLAs, and performance.
Support Data Science, BI, and ML teams with reliable data and semantic layers.
Collaborate closely with Data Engineering, Data Science, MLE, and Product Owners for integrated and value-driven deliveries.
Required Qualifications
Technical Skills
Advanced Data Modeling and Architecture: Expertise in star schema, dimensional modeling, medallion architecture, schema evolution management, and semantic layer design.
Large-Scale Semantic Layer & Data Model Optimization: Building and optimizing large-scale models, ensuring performance, consistency, and governance.
Pipeline Orchestration and Automation: Experience with ETL/ELT tools such as Azure Data Factory, Apache Airflow, Microsoft Fabric, Databricks Workflows.
SQL Expertise & Performance Engineering: Proficiency in query tuning, partitioning, clustering, and handling large volumes of data with scalable SQL.
Advanced Transformations with Python/Spark: Expertise in PySpark, Spark SQL, and structured Python for advanced data transformations.
CI/CD and Versioning for Data Pipelines: Experience implementing CI/CD pipelines, version control, and DevOps best practices for data.
Data Quality Frameworks & Observability: Rule definition, automated data validation, end-to-end monitoring, and observability.
Data Governance, Cataloging, and Lineage: Practical use of tools like Microsoft Purview or Unity Catalog for governance, cataloging, and lineage tracing.
BI Modeling and Performance: Advanced semantic modeling in Power BI, DAX optimization, and efficient analytical model design.
Cloud Data Warehousing and Technical Architecture: Hands-on experience with platforms like BigQuery, Snowflake, Synapse, Delta Lake, ADLS, and Redshift; understanding system interdependencies.
Soft Skills
Ability to align and bridge the needs of business, BI, Data Science, and Data Engineering teams, translating requests into actionable technical requirements.
Support growth of junior profiles through guidance and functional reviews, promoting collective improvement in output quality.
Demonstrate accountability for delivering high-quality, consistent, and stable models and analyses while sustaining team trust and reliability.
Tackle ambiguous issues with a structured approach, identify root causes, and propose scalable and effective solutions.
Easily adapt to shifting priorities, efficiently generate workload plans, and proactively communicate risks to maintain smooth operations.
Experience Requirements
Senior Analytics Engineer
Minimum 5+ years in data analytics environments with a proven record of architecting and deploying production-grade analytical solutions.
Mid Analytics Engineer
Minimum 3+ years in data analytics environments with hands-on contribution to reliable data solutions.
Other Requirements
Educational Background: Degree in Data Science, Computer Science, Analytics, Machine Learning, or a related domain.
Language Skills: Proficiency in English at a minimum B2 level or higher.