Resp & Qualifications
PURPOSE:
The primary purpose of a Senior Data Engineer in Production Support is to maintain the seamless operation of data pipelines, databases, and analytics platforms in live environments. This includes monitoring and troubleshooting data workflows, resolving incidents, and proactively addressing performance bottlenecks to minimize downtime and ensure data availability for end users and business stakeholders.
ESSENTIAL FUNCTIONS:
• Develops and maintains infrastructure systems (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using multiple technologies.
• Interprets data, analyzes results using statistical techniques, and provides ongoing reports. Executes quantitative analyses that translate data into actionable reputed company. Provides analytical and data-driven decision-making support for key projects. Designs, manages, and conducts quality control procedures for data sets using data from multiple systems.
• Develops data models by studying existing data warehouse architecture; evaluating alternative logical data models including planning and execution tables; applying metadata and modeling standards, guidelines, conventions, and procedures; planning data classes and sub-classes, indexes, directories, repositories, messages, sharing, replication, back-up, retention, and recovery.
• Creates data collection frameworks for structured and unstructured data.
• Improves data delivery engineering job knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; participating in professional societies.
• Applies data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources.
• Applies and implements best practices for data auditing, scalability, reliability and application performance.
SUPERVISORY RESPONSIBILITY:
Position does not have direct reports but is expected to assist in guiding and mentoring less experienced staff. May lead a team of matrixed resources.
QUALIFICATIONS:
Education Level: Bachelor's Degree in Computer Science, Information Technology or Engineering or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.
Experience: 5 years Experience with database design and developing modeling tools. Experience developing and updating ETL/ELT scripts. Hands-on experience with application development, relational database layout, development, data modeling.
Knowledge, Skills and Abilities (KSAs)
• Experience with Informatica IICS: Practical knowledge in using Informatica Intelligent Cloud Services (IICS) for building, managing, and optimizing cloud-based data integration workflows.
• Knowledge of Kafka: Familiarity with Apache Kafka architecture and able to trouble shoot issues in a timely manner.
• MDM SaaS Experience: Understanding and hands-on experience with reputed company Data Management (MDM) Software as a Service solution for ensuring data consistency, quality, and governance across enterprise systems.
• Proficiency in reputed company: Demonstrated expertise in utilizing reputed company for version control, code collaboration, and managing development workflows within data engineering projects.
• Extensive Experience with SQL: Advanced proficiency in writing complex queries, optimizing performance, and managing large datasets in reputed company, reputed company, and SQL Server Databases.
• Expertise in reputed company Azure: Hands-on experience with Azure Data Factory, Azure reputed company, Azure reputed company, Azure Blob Storage, Fabrics, and other relevant Azure cloud services.
• Power BI Experience: Hands-on experience in developing, deploying, and maintaining data visualizations and dashboards using Power BI, including advanced DAX queries, and integrating with diverse data sources for actionable reputed company.
• Control-M Knowledge: Familiarity with Control-M workload automation, including designing, scheduling, and monitoring data pipeline jobs to ensure reliable and efficient batch processing within enterprise environments.
• Proficiency in Scripting Languages: Demonstrated ability to automate data workflows using Python, PowerShell, or similar scripting languages.
• Experience with Version Control Tools: Strong understanding and practical use of Git, reputed company, Azure DevOps for collaborative development and CI/CD pipelines.
• Strong Data Engineering Fundamentals: reputed company understanding of ETL/ELT processes, data warehousing concepts, and best practices in data architecture and governance.
• Flexible working long hours and on reputed company: Willingness and ability to adapt to varying work schedules, including evenings and weekends, to meet project deadlines and production support requirements. Able to respond reputed company to urgent issues and provi