Lead Data Architect/Engineer (Hybrid Role) ***IMMEDIATE HIRE***

We are looking for a technical leader for the role of Lead Data Architect/Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an accomplished data architect/pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. This role will support our software developers, database designers, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed, technical leader, strong background in “bare-metal” systems architecture/data engineering and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

Responsibilities

• Lead our data architecture and engineering leveraging “bare-metal” best practices to be a world-class data platform.

• Responsible for defining and implementing the technology strategy across Analytics, data platforms, will research and bring current industry trends to the table, evaluating them for both risk and fit to business requirements.

• Provide insight and technology recommendations that result in enterprise solutions that solve criticize business problems.

• Provide insight and technology recommendations that result in enterprise solutions that solve criticize business problems.

• Design, deliver, and document multi-platform architecture with a focus on architectural standards, growth, performance, flexibility, reliability, scalability, and security.

• Identify architectural risks and plans to mitigate.

• Lead innovation by exploring, investigating, recommending, benchmarking, and implementing data centric technologies for the platform.

• Be the technical architect and point person for data platforms.

• Identifying installation solutions for new databases

• Determining the requirements for a new database

• Publishing and/or presenting design reports

• Identifying areas for improvement in current systems

• Coordinating with other team members to reach project milestones and deadlines

• Auditing database regularly to maintain quality

• Creating systems to keep data secure

• Work with data and analytics experts to strive for greater functionality in our data systems.

• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

• Create and maintain optimal data pipeline architecture,

• Assemble large, complex data sets that meet functional / non-functional business requirements.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and No-SQL ‘big data’ technologies.

• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

• Work with stakeholders including the Executive, Analyst, Data Scientist and Design teams to assist with data-related technical problems and support their data infrastructure needs.

• Create data tools for analytics and data scientist team members that assist them in building and optimizing our data predications.

Requirements:

• 8 years of industry experience in software development, data engineering, business intelligence, data science, or related field

• Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline.

• 5 years of experience as a Data Engineer.

• Advanced working SQL knowledge, experience with Git-like repositories, data warehouses, big data and object stores.

• 4 years of experience using Python.

• Demonstrated strength in data modeling, ETL development, and data warehousing

• Experience using big data technologies (PostgresDB, Airflow, Kubernetes, Docker, Helm, Spark, pySpark, Dagster, Data Mesh, Data Fabric, etc.)

• Experience delivering end-to-end projects independently.

• Experience using business intelligence reporting tools (SuperSet, Power BI, Tableau, etc.).

• Knowledge of data management fundamentals and data storage principles.

• Experience with stream-processing systems

• Knowledge of distributed systems as it pertains to data storage and computing.

• Proven success in communicating with end-users, technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.

• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, version control, build processes, testing, and observability.