Accountabilities:

Lead and provide subject matter expertise for data collection, validation, visualization, and analytics initiatives.
Apply structured methodologies to plan, analyze, design, and develop enterprise-wide information systems and data engineering solutions.
Develop advanced analytical techniques and methodologies to address complex business and technical challenges.
Conduct strategic systems planning, business information planning, and business analysis to support organizational objectives.
Organize, process, and analyze large volumes of structured and unstructured datasets using advanced data analytics tools and technologies.
Locate, access, integrate, merge, clean, and standardize data from multiple sources while developing meaningful derived metrics.
Design, develop, and implement data collection, processing, and analysis tools using Python, Databricks, SQL, Scala, R, and Java.
Design, script, debug, test, and analyze data engineering solutions to ensure accuracy, reliability, and performance.
Develop and implement machine learning-based tools, workflows, and processes to enhance analytical capabilities.
Apply distributed and parallel processing technologies, particularly Apache Spark, to process large datasets and support complex big data analytics requirements.
Perform SQL Server data imports and manage data ingestion from CSV and TXT files.
Leverage Microsoft Excel and Google Workspace tools for data analysis, reporting, and collaboration.
Utilize supporting technologies and platforms, including Pentaho for data integration and transformation, Azure Data Studio, GitHub, and Smartsheet, as required.
Document technical requirements, project activities, completed tasks, workflows, methodologies, and implementation details accurately.
Communicate technical findings, project progress, and analytical recommendations effectively to technical teams and business stakeholders.
Operate independently as a technical subject matter expert, taking ownership of assigned initiatives and delivering solutions in a dynamic, fast-paced environment.

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical discipline.
At least 7 years of professional experience, including a minimum of 3 years of specialized experience in data engineering, data analytics, or related technical fields.
Active Secret security clearance is required.
Strong expertise in organizing, processing, and analyzing large volumes of structured and unstructured data using advanced analytical tools.
Demonstrated experience locating, accessing, integrating, merging, cleaning, and standardizing data from multiple sources, as well as developing derived metrics.
Advanced proficiency in Python, Databricks, and SQL, with working knowledge of Scala, R, and Java for data collection, engineering, and analytical applications.
Strong experience designing, scripting, debugging, implementing, and maintaining data engineering solutions.
Practical experience implementing and developing machine learning-based tools, models, or processes.
Solid understanding of distributed and parallel processing technologies, particularly Apache Spark, and their application to large-scale data processing and big data analytics.
Experience working with SQL Server and importing data from CSV and TXT files.
Strong proficiency in Microsoft Excel and Google Workspace applications.
Familiarity with Pentaho, Azure Data Studio, GitHub, and Smartsheet is an advantage.
Excellent technical documentation skills, with the ability to clearly record project requirements, methodologies, completed work, and technical processes.
Strong written and verbal communication skills, with the ability to translate complex technical concepts into clear information for different stakeholders.
Excellent analytical thinking, problem-solving, and organizational skills.
Ability to work independently, manage competing priorities, and take initiative in a fast-paced and entrepreneurial environment.
Strong attention to detail and commitment to delivering accurate, reliable, and high-quality data solutions.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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