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 looking for a Senior or Lead Data Engineer with strong expertise in cloud-native data engineering and modern Microsoft data ecosystems. This role focuses on designing, building, and optimizing scalable data pipelines and architectures that power analytics and business decision-making. The ideal candidate is comfortable owning end-to-end data lifecycle development, from ingestion to orchestration, and has the leadership and technical vision to guide the evolution of enterprise data platforms.
Requirements
Requirements
Education: University degree (minimum 3 years) in Engineering, Information Technology, Management, or Economics.
Minimum 5 years of experience in data engineering, focusing on cloud-native solutions and scalable architecture.
Experience leading or mentoring teams (for Lead profiles).
Technical Skills
Strong expertise in data architecture and design, covering ingestion, modeling, storage, and orchestration (e.g., Medallion architecture).
Proven experience with Microsoft data technologies, including Fabric, Azure Data Factory, and Synapse.
Solid knowledge of data warehousing and data lake solutions such as Azure Data Lake, Delta Lake, BigQuery, or Amazon Redshift.
Proficiency in Python (using data-oriented libraries such as Pandas, Boto3), SQL, and Spark.
Strong understanding of RDBMS (Oracle, MS SQL Server) or NoSQL solutions (MongoDB, ElasticSearch, Google BigQuery).
Experience applying DevOps/DataOps practices, especially CI/CD pipelines for data workflows.
Ability to implement data validation, lineage tracking, and monitoring at scale.
Proven experience optimizing pipelines and storage for performance, cost, and reliability.
Soft Skills
Ability to make and defend strategic technical decisions with clear justifications.
Capability to translate complex engineering concepts for non-technical audiences.
Experience mentoring and uplifting junior/mid-level engineers while setting technical standards.
Strong problem-solving mindset, able to break down complex issues into actionable steps.
Accountability for long-term results and a proactive approach to platform evolution.