Data Engineer II

The Data Engineer will develop and implement large scale data lakes data warehouses data marts data pipelines and associated visualizations and reports using state of the art data engineering principles techniques big-data platforms and tools. Through these capabilities the Data Engineer will directly support solutions to Data Science Business Intelligence and ad-hoc business problems as well as front line user interface systems. The Data Engineer will ensure the creation and maintenance of consistent up-to-date easy to use and high-quality data to drive measurable business benefits.

Roles and Responsibilities :

• Create large scale data engineering systems and capabilities from the ground up that will improve business effectiveness and performance.

• Support near and long-term data architecture to support Global Data Science and Business Intelligence and create an industry-leading technical data engineering platform that leverages the best cutting-edge cloud technologies and integrates with legacy systems such as mainframes.

• Leverage knowledge of the electronics distribution industry and value chain to specialize data engineering capabilities for TTIs global business needs.

• Support TTIs business goals by collecting securing filtering transforming organizing validating and projecting internal and external data to and from business transactions business intelligence and data science platforms in a consistent timely secure and scalable manner.

• Capture and organize fine-grained drivers of TTIs revenue cost gross profit operational efficiency market share and customer experience in highly scalable low-latency and easy-to-consume data sets.

• Create data marts consisting of structured semi-structured and unstructured data along with pertinent high-performance data transformation pipelines for machine learning and operations research applications impacting business/operational decisions globally.

• Mitigate obsolescence risk through technical research into the latest methods and tools for data engineering.

• Ensure data consistency validity and accuracy by mitigating various risks including but not limited to duplication missing values and outliers in data.

• Build a high degree of confidence in the quality of data. Create alerts and data quality reports to inform stakeholder in a timely manner of anomalies and aberrations in data based on statistical distributions of nominal interval and ratio metrics across multiple categorical and temporal dimensions.

• Create and maintain effective documentation and reports pertinent to TTIs data engineering capabilities and best practices.

• Comply with and implement best practices methods standards and procedures related to data engineering.

• Collaborate with internal and external stakeholders across diverse global functional teams and ensure compatibility and integration of data engineering capabilities with existing and future IT systems.

• Prepare high-level and detail-level project plans and ensure that each project objective is being completed within the agreed upon deadlines.

• Subject matter expert for team job functions.

• Initiates establishes and maintains highly effective relationships with business contacts of various cultures and at all levels.

• Flexible to meet the changing needs of the business and willingness to take on new responsibilities and assignments.

SKILLS & CERTIFICATIONS

• Strong interest and acumen for solving large-scale data engineering problems.

• Hands-on technical and functional experience in building large scale data engineering capabilities in diverse big-data environments

• Strong hands-on expertise in data engineering:

• Enterprise grade ETL tools

• Cloud platforms (Microsoft Azure in particular)

• Deep knowledge of and solid hands-on experience with Data Architecture Database design SQL stored procedures Python programming No-SQL databases columnar databases database internals database query optimization and other related methods tools and techniques

• Experience with and deep knowledge of organizing High & Low Velocity Volume Variety Veracity and Value (the Five Vs) data across cold warm and hot storage.

• Extensive hands-on experience creating solutions in collaboration with Data Scientists and Business Intelligence professionals.

• Experience in problem solving and delivering practical solutions.

• Team player who enjoys working in a collaborative agile environment

• Excellent communication skills with the ability to explain the significance of data in a way that can be easily understood by others.

• Desire and ability to learn continuously and upgrade expertise in various technical/business concepts techniques and tools relevant to TTIs business.

EDUCATION & EXPERIENCE

• 5 years of experience.

• Bachelors degree in computer science or equivalent.

• Should have Big Data experience with Snowflake Teradata Netezza etc.

Should have conceptual data modelling and data engineering experience