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Middle Data Engineer
Sigma Software Group. Design and develop scalable, reliable data platforms and pipelines for analytics and operations .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing scalable data platforms and pipelines using Azure technologies, Apache Spark, and SQL. Proficient in data modeling, ETL/ELT processes, and ensuring data quality and consistency across multiple sources.
Highest-signal resume keywords
Data EngineeringApache Spark/PySparkAzure Data FactorySQLData Modeling
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringSQLPythonApache SparkDatabricksETL/ELT DesignDimensional ModelingData WarehousingData Lake ArchitecturesDatabase Development
Soft Skills
CollaborationCommunication
Tools & Technologies
Azure Data FactoryAzure SynapseAzure Event HubAzure Data Lake StorageAirflow
Industry Keywords
Data ProcessingData PipelinesAnalyticsOperational ReliabilityWorkflow Orchestration
Tech Stack
Tools & technologiesAirflowApacheAzureCloudETLPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Design and develop scalable, reliable data platforms and pipelines for analytics and operations
- Implement data processing workflows using distributed frameworks such as Apache Spark/pySpark and Databricks
- Evolve the organization's cloud data platform using Azure technologies, including Data Factory, Synapse, Event Hub, and Azure Data Lake Storage
- Model data to support analytics, reporting, and downstream consumption
- Integrate and process data from multiple sources while ensuring quality and consistency
- Monitor and optimize pipeline performance, reliability, and scalability
- Collaborate with analysts, scientists, and engineers to translate requirements into solutions
- Improve data engineering standards, testing, and operational reliability
- Evaluate and introduce new tools and technologies in the data engineering ecosystem
Requirements
What you’ll need- 4+ years of hands-on experience in data engineering or building data processing platforms
- Strong SQL skills
- Solid Python experience for pipeline development
- Experience with distributed processing frameworks, including Apache Spark/pySpark; Databricks preferred
- Practical experience designing and implementing pipelines in cloud environments; Azure preferred
- Experience with production-scale analytical systems and data modeling
- Understanding of ETL/ELT design, dimensional modeling, and data warehousing principles
- Experience with modern data lake architectures and formats, including Parquet and JSON
- Familiarity with workflow orchestration tools, including Airflow
- Experience with database development and optimization
- Ability to design scalable solutions with minimal supervision
- Strong collaboration and communication skills
- Professional proficiency in English
Benefits
Comp & perks- Professional growth opportunities
- Supportive environment
- Competitive benefits
- Remote work option