Data Engineer (II)

About the role

As a Data Engineer at Strong Tower Consulting, you will independently execute end-to-end tasks integrated into large overarching projects. You participate in data product, infrastructure, and solution design and development with minimal assistance, ensuring completed work meets high-quality standards. You are seen as a solid individual contributor, demonstrating working knowledge of core data concepts, technologies, and methods, translating business requirements into technical data solutions, and mastering one major skill outside of core coding (e.g., monitoring, documentation, integration testing).

Responsibilities

• Provide ongoing support for data users through maintenance of reports, queries, and dashboards with minimal guidance.
• Execute plans for dependency changes (e.g., system migrations).
• Design and implement business solutions and infrastructure to build and scale common frameworks with minimal guidance.
• Partner with upstream data providers to establish new source data pipelines.
• Follow and improve upon local technical best practices, including making data discoverable, considering the lifecycle of data, and managing master data well.
• Design, build, operationalize, secure, and monitor data processing systems with emphasis on security and compliance, scalability and efficiency, reliability and fidelity, and flexibility and portability.
• Leverage, deploy, and continuously train pre-existing machine learning models.
• Learn and implement new storage/MPP systems/ML serving systems with minimal guidance.
• Perform data analysis and profiling utilizing relevant tools, leveraging custom data infrastructure, or existing data models with minimal guidance.
• Work with clients to understand their needs, clarify requirements, or direct to more suitable channels.
• Enable data-driven decision-making by collecting, transforming, and publishing data.
• Create and/or consult in creating data visualizations and visualization features using internal BI tools like PLX, Datastudio, and external tools like Tableau and Looker, with minimal guidance.
• Develop and maintain data models, pipelines, and exchange formats to assist in visualization, analysis, interpretation of data, and use in ML training/models, with some guidance.
• Consult with users, partners, or decision makers to identify data sources, required data elements, or data validation standards, with minimal guidance.
• Consult with application engineers to understand and influence logging/transactional storage.
• Consult with Data Scientists on ML training and feature engineering for ML models.

Requirements

• Proficiency in code comprehension and programming skills.
• Strong information gathering skills.
• Experience with big data infrastructure.
• Knowledge of Machine Learning.
• Stakeholder management experience.
• Project management experience.
• Data exploration skills.
• Experience in data pipeline (ETL) design and data modeling.
• Familiarity with statistics and BI tools.

Skills

• Python coding
• Google Cloud Platform (GCP) experience
• Experience working with AI/ML models

Benefits

• Competitive Package: Approximately a full package value of $213,000 – $254,000 annually, based on a $89–$108 per hour rate.
• New Hire Referral Bonus and New Project Referral Bonus
• Health and Wellness Insurance Plans: Two PPO options for Medical, Dental, and Vision coverage.
• Life and Disability Insurance: Comprehensive coverage including Life, Long-Term, and Short-Term Disability, provided at no cost.
• 401K Plan: Retirement savings plan.
• Health and Child Care Savings Accounts: Flexible spending accounts.
• Additional Savings: Access to ADP discount benefits.
• Professional Training: Over 400 free courses for career advancement.
• Mentor/Mentee Program: Supportive professional and personal growth network.
• Female Leadership Program: Initiative to empower women in leadership positions.
• Carbon Program: Commitment to sustainability.
• Charity Program: Community engagement opportunities.
• SWAG & Equipment: Tools and Strong Tower branded items.