Full Job Description
Job Summary
We are seeking a highly skilled and motivated Data Engineer to join our dynamic team at
Speria MTech. The ideal candidate will play a crucial role in designing, building,
and maintaining scalable data pipelines and platforms that support machine learning,
optimization, and operational reporting systems. This role focuses on transforming data from
sensors, controllers, and enterprise systems into high-quality datasets using primarily batch
and scheduled processing workflows, with support for evolving near real-time use cases.
We seek a solution-oriented individual who can provide answers rather than just identify
problems. Embracing continuous change is key, as innovation and improvement are integral
to Speria MTech's culture. This person should have a service-minded attitude, demonstrating
a passion for enhancing the work of others and simplifying processes for stakeholders.
Essential Functions & Responsibilities
Essential responsibilities include and functions of the Data Engineer are:
• Design and build batch and near real-time data pipelines
• Develop transformation workflows for high-quality datasets
• Ensure data quality, integrity, and reliability
• Collaborate with MLEs for feature data readiness
• Implement data monitoring and anomaly detection
• Support synthetic data for testing and simulation
• Optimize pipelines to remove redundancy and reduce costs
• Improve performance, scalability, and efficiency
• Maintain pipeline reliability and documentation
Qualifications, Skills, and Experience
• Bachelor's degree in Computer Science, Engineering, or related field
• 2-4 years experience in data engineering or data systems
• Experience with Apache Spark and large-scale data processing
• Experience building batch pipelines in production
• Experience with cloud platforms (e.g., Azure, Databricks)
• Strong Python programming skills
• SQL and Apache Spark expertise
Preferred Skills
• Experience with batch and scheduled pipelines
• Experience optimizing pipeline performance and cost
• Familiarity with Azure ecosystem (Event Hub, Cosmos DB, Functions)
• Experience with data quality monitoring and validation
• Strong problem-solving and collaboration skills