Strong Middle/Senior Data Engineer at DataArt
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Our client is a successful, self-funded specialty food and wellness company, rapidly growing with a team of over 550 people. Originally established in Newark, New Jersey during the Great Depression, they began by selling premium nuts at an open-air market.
The ideal candidate will play a key role in establishing the groundwork for diverse types of analysis. This includes conducting comprehensive cross-channel analysis of media interaction logs, optimizing paid media efforts, and distilling purchase data to gain deeper insights into customer behavior. Additionally, the candidate will evaluate warehouse and sourcing data to enhance operational efficiency. You’ll also be expected to brainstorm innovative methods to improve our data systems, supporting better business decisions and enhancing the overall shopping experience.
Responsibilities
- Apply your engineering expertise to solve large-scale business problems. Drive design and architecture discussions and build alignment on complex technical decisions
- Design, implement, validate, and deploy software solutions to enhance our reporting and analytics systems. This includes new features and architectural improvements for our data pipeline and analytics tools, such as Looker, dbt, Databricks, Fivetran, Airbyte, and AWS Redshift
- Provide technical leadership in data architecture and help establish best practices for data modeling, storage, and retrieval
- Collaborate with cross-functional teams to understand data needs and design solutions that meet business requirements
- Drive the adoption of advanced analytics techniques and technologies to unlock insights from large datasets
- Perform design and code reviews to ensure quality and scalability
- Lead the design of data governance policies and procedures. Help establish and enforce data security and privacy protocols to safeguard sensitive information
- Further agile and DevOps practices to ensure efficient and high-quality data engineering processes
- Support on-call assignments and operational management
- Collaborate with business analysts and product owners to assist with measuring experiments to vet hypotheses
- Mentor, lead, and train other members of the data engineering team
Requirements
- Bachelor’s degree required in Computer Science, Software Engineering, or related field
- 3+ years of experience in data engineering working with big data systems that can process and transform data at scale
- Deep knowledge of analytics technologies, modeling techniques, data streaming and other ingestion approaches, data warehousing concepts, cloud platforms (AWS preferred), and proven experience with data architecture including data pipelines, dimensional modeling, and dependency management
- Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.)
- Experience automating data integration using APIs
- Proficiency in programming languages such as SQL and Python in an analytics context
- Experience handling operational aspects of large-scale systems focusing on observability, tech debt management, code refactoring, and robust software development and release processes
- Experience articulating technically complex topics in an easy-to-understand way via written and verbal communication methods
- Proven track record of mentorship, leadership, and ownership within teams and organizations
Nice to have
- Master’s degree preferred in a related field
We offer
• Professional Development:
— Experienced colleagues who are ready to share knowledge;
— The ability to switch projects, technology stacks, try yourself in different roles;
— More than 150 workplaces for advanced training;
— Study and practice of English: courses and communication with colleagues and clients from different countries;
— Support of speakers who make presentations at conferences and meetings of technology communities.
• The ability to focus on your work: a lack of bureaucracy and micromanagement, and convenient corporate services;
• Friendly atmosphere, concern for the comfort of specialists;
• Flexible schedule (there are core mandatory hours), the ability to work remotely upon agreement with colleagues.
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