Data Engineer

Description:

Data Engineer is primarily responsible for the robust design, construction, and
optimization of the organization’s data architecture, including data warehouses and reliable
ETL/ELT pipelines. This role is essential for ensuring data quality, availability, and security.
Secondarily, the role involves leveraging technical data skills to perform advanced analytics,
generate critical financial and market intelligence, and translate complex data into clear,
strategic recommendations for business leaders. A successful candidate will possess a
strong command of scalable data systems and demonstrate the analytical capability to
derive actionable insights from large datasets. This role is also responsible for exemplifying
excellent customer service and the Company core values, culture, policy and procedures at
all times.

What will you do?

● Design, develop, and analyze the enterprise data architecture, optimizing data
warehouses and data lakes for scalability and query performance.
● Develop, deploy, and maintain robust Data tools, interfaces, and automated ETL/ELT
pipelines.
● Write, test, and perform advanced SQL queries to transform raw data into curated,
high-quality information assets.
● Maintain clear, comprehensive technical documentation for all data assets, database
schemas, and ingestion processes.
● Map, catalog, and manage various organizational databases and data flow streams.
● Collaborate closely with different teams to translate analytical requirements into
robust, automated reporting and dashboard solutions.
● Translate complex technical and analytical concepts into simple, actionable language
for business stakeholders.
● Use project management and leadership skills to drive data projects to successful
completion.
● Other duties as prescribed – Please note this job description is not designed to cover
or contain a comprehensive listing of activities, duties or responsibilities that are
required of the employee for this job. Duties, responsibilities and activities may
change at any time with or without notice.

Requirements:

• Bachelor's Degree (B.A.) or equivalent four-year degree in Data Engineering, Computer Science, or a related field (Business Information or MIS acceptable with strong technical experience), Masters degree preferred.
• 5+ year(s) of progressive experience in Data Engineering, Data Architecture, or a similar role, with a proven emphasis on building and maintaining scalable data infrastructure.
• Expertise in core AWS services for data processing, orchestration, and AI/ML, specifically: Glue, Redshift, Athena, Step Functions, Lambda, SageMaker, Bedrock, and Agent Core.
• Expert proficiency in SQL and demonstrable experience in database administration (DB/DBA).
• Proven track record of designing, building, and deploying scalable Data solutions (e.g., ETL/ELT tools, reporting tools).
• Experience with Python, Java, or R for data manipulation, scripting, and pipeline development.
• Strong working knowledge of Computer Science fundamentals.
• Proficiency in data visualization software (e.g., PowerBI, Superset, QuickSuite) and experience delivering reporting and dashboard solutions.
• Deep experience working with and optimizing data warehouses and/or data lakes to extract trends, validate data accuracy, and support predictive modeling.
• Strong analytical, deductive reasoning, critical thinking, innovation, and problem-solving skills.
• Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, and sequence-based models.
• Organized and self-motivated quick-study with ability to define goals, manage projects, train others and prioritize work.
• Advanced English.

Nice to have: