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Senior Matillion Developer

Key Responsibilities:

ETL Design & Development: Lead the design, development, and optimization of Matillion ETL pipelines for data extraction, transformation, and loading (ETL) from multiple sources into cloud-based data warehouses (e.g., AWS Redshift, Google BigQuery, Snowflake). Data Integration: Work closely with cross-functional teams, including business analysts, data engineers, and solution architects, to integrate data from diverse sources into a unified cloud data platform. Cloud Data Platforms: Work extensively with cloud-native data tools and services on platforms like AWS, Azure, and Google Cloud to build scalable data pipelines, leveraging services such as AWS S3, Redshift, Azure Data Lake, and BigQuery. Optimization & Performance Tuning: Optimize ETL workflows and performance in Matillion to meet business objectives, with a focus on reducing processing time and improving scalability. Data Quality & Governance: Ensure data consistency, quality, and governance throughout the data pipeline by implementing robust error handling, logging, and data validation practices in Matillion. Mentorship & Training: Provide leadership to junior developers and guide them on best practices for Matillion ETL, data integration, and cloud technologies. Foster a culture of continuous learning within the team. Collaboration with Stakeholders: Interface with internal stakeholders and clients to understand business requirements and provide technical solutions. Ensure timely and successful project delivery with clear communication. Documentation & Best Practices: Document all ETL workflows, data transformation logic, and technical specifications. Promote and follow best practices for coding, deployment, and version control. Troubleshooting & Support: Diagnose and resolve complex data issues, performance bottlenecks, and errors in the ETL processes. Provide ongoing support for production environments.
 

Key Skills & Qualifications:

ETL Expertise: Strong hands-on experience with Matillion ETL (version 4.x or later), or other ETL tools such as Informatica PowerCenter, SSIS, IBM DataStage, or Talend. Cloud Data Platforms: In-depth experience with cloud-based data platforms like AWS (Redshift, S3), Google Cloud Platform (BigQuery, Dataflow), or Microsoft Azure (Azure Data Lake, Synapse Analytics). SQL/PLSQL Expertise: Advanced proficiency in SQL and PL/SQL for complex data querying, manipulation, and optimization. Performance Tuning: Proven ability to optimize ETL workflows and troubleshoot performance issues, ensuring data pipelines are efficient, scalable, and error-free. Data Migration & Transformation: Extensive experience with data migration, data profiling, and transforming data from source systems to a data warehouse. Big Data & Hadoop Technologies: Familiarity with big data frameworks like Spark, Hadoop, Hive, Impala, Yarn, and HDFS is a plus. Scripting & Automation: Proficiency in scripting languages (e.g., Python, Bash, or Java) for custom transformations, automation, and orchestration within ETL workflows. Data Modeling: Strong understanding of data modeling principles, including star schema, snowflake schema, and dimensional modeling. Error Handling & Debugging: Experience in error handling, debugging, and optimizing complex ETL jobs within Matillion and other ETL tools. Cloud Certification (Preferred): Certification in AWS, Azure, or Google Cloud is desirable.
 

Experience & Qualifications:

Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Master’s degree or certifications (e.g., AWS Certified Data Analytics) is a plus. Experience: 5+ years of experience in ETL development, data engineering, or data integration. At least 2-3 years of hands-on experience with Matillion ETL in cloud environments. Client-facing Experience: Proven ability to work directly with clients, gathering requirements, managing expectations, and delivering high-quality data solutions. Project Experience: Previous experience working in fast-paced environments on projects with short delivery timelines (6-12 months). Agile Methodology: Experience working in an Agile development environment, with familiarity with Scrum or Kanban practices.
 

Key Competencies:

Problem Solving: Ability to think critically and resolve complex data integration and performance issues quickly and efficiently. Collaboration: Strong teamwork and collaboration skills with the ability to work cross-functionally and build relationships with both technical and business teams. Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Adaptability & Learning: Enthusiastic about learning new technologies, frameworks, and industry trends to stay ahead in the fast-evolving cloud and data engineering space.

 

 

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