Senior Data Engineer specializing in Azure Data Factory and SQL

Job Description

This position develops batch and real-time data pipelines utilizing various data analytics processing frameworks in support of Data Science and Machine Learning practices. The role assists in the integration of data from various internal and external data sources, performs extract, transform, load (ETL) data conversions, facilitates data cleansing and enrichment, and handles full systems life cycle management, including analysis, technical requirements, design, coding, testing, and implementation of systems and applications software. The position synthesizes disparate data sources to create reusable and reproducible data assets and assists the Data Science community with analytical model feature tuning.

Responsibilities

• Contribute to data engineering projects and build solutions by leveraging foundational knowledge in software/application development and proficiency in programming languages used for statistical modeling and analysis, data warehousing and cloud solutions.
• Collaborate effectively, produce data engineering documentation, gather requirements, organize data, and define project scope.
• Perform data analysis and present findings to stakeholders to support business needs.
• Participate in the integration of data for data engineering projects.
• Understand and utilize analytic reporting tools and technologies.
• Assist with data engineering maintenance and support.
• Assist in defining data interconnections between organizations’ operational and business functions.
• Assist in backup and recovery and utilize technology solutions to perform POC analysis.

Qualifications

• Understanding of database systems and data warehousing solutions.
• Understanding of data life cycle stages—data collection, transformation, analysis, secure storage, and data accessibility.
• Understanding of the data environment to ensure scalability for data throughput, large‑scale analysis, real‑time predictions, insights, data security, regulations, and compliance.
• Experience building a data platform, ensuring data security in motion and at rest, automating data compliance and auditing, and developing scalable data warehousing solutions.
• Familiarity with analytics reporting technologies and environments (e.g., Power BI, Looker, Qlik).
• Basic knowledge of algorithms and data structures to support the organization’s overall data function.
• Knowledge of data filtering and data optimization.
• Familiarity with a cloud services platform (e.g., GCP, Azure, or AWS) and all stages of the data life cycle.
• Understanding of ETL tools and ability to pull data from various sources and load transformed data into a database or BI platform.
• Familiarity with machine learning algorithms used by data scientists for predictions.
• Ability to build data APIs to enable data scientists and BI analysts to query data.
• Proficiency in programming languages used for statistical analysis and modeling such as Python, Java, Scala, or C++.
• Understanding of distributed systems basics.
• Bachelor’s degree in MIS, mathematics, statistics, computer science, international equivalent, or equivalent work experience.

Employee Type

Permanent

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