Overview
Methods+Mastery is seeking an experienced Data Engineer with a strong background in building scalable data pipelines that process unstructured text data to join our talented team. The ideal candidate will be comfortable taking on leadership roles in ambiguous tasks. This is an excellent opportunity to help shape the future of social media and digital marketing analytics while working with a diverse and passionate team.
Our new Data Engineer will work directly with members of the multi-disciplinary Methods+Mastery team to produce work for top clients in an entrepreneurial and collaborative environment that values team above all. This work will include counseling Methods+Mastery team members on feasible data management solutions for client projects and collaborating with our Data Scientist to build out data pipelines.
Methods+Mastery is an entrepreneurial, collaborative environment that values talented, creative people who like to work with others to create cutting-edge programs for our clients. We’re seeking someone who is passionate about social, data and analytic tools. Someone who has an innate curiosity and the desire to find out "why?” Our team is growing at an amazing rate, and this is an opportunity to produce work for top clients in an entrepreneurial and collaborative environment that values team above all. We do great work – and hire only great people, too.
Methods+Mastery is actively committed to increasing our team’s diversity, aggressively eliminating systemic barriers to equity, and fostering a culture where different backgrounds and perspectives are respected and celebrated. We firmly believe a team of many diverse perspectives not only makes M+M a better place to work, it is also critically important for producing creative and thoughtful work that represents the world we live in. To that end, we strongly encourage applications from women, people of color, members of the LGBTQ+ community, veterans, individuals with disabilities, and neurodivergent people.
The anticipated salary range for this position is $150,000 - $180,000.
Salary is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications, and geography. A range of medical, dental, vision, 401(k) matching, paid time off, and/or other benefits also are available.
Sound like what you’re looking for?
Responsibilities
- Design, build, and maintain scalable data pipelines, ETL processes, and data integration solutions to support our marketing and business analytics needs.
- Leverage cloud computing platforms (e.g., GCP, Azure) to develop and deploy data infrastructure and applications.
- Collaborate with cross-functional teams, including analytics, research, and strategy, to define data requirements, create data models, and implement data solutions.
- Optimize data storage, processing, and retrieval performance to ensure efficient and reliable access to high-quality data.
- Develop and maintain data documentation, including data artifacts, data lineage, and data quality metrics
- Proactively identify and address data-related challenges and opportunities, taking the initiative to lead ambiguous tasks and drive projects to completion
- Stay up-to-date with the latest industry trends, technologies, and best practices in data engineering and marketing analytics to ensure the company remains competitive
- Support ad-hoc data requests and analysis from various business units, ensuring timely and accurate delivery of insights
- Participate in the evaluation and selection of data-related tools and technologies, and contribute to the development of data engineering best practices and standards
Qualifications
The ideal candidate is keenly strategic, versatile, and insights-driven; someone who thrives in an energetic, fast-paced entrepreneurial environment.
Must-haves:
- Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or a related quantitative discipline
- 2+ years of professional experience as a Data Engineer utilizing Python, R, Rust, C++, or Scala in cloud computing platforms (AWS, GCP, Azure)
- Deploying and productionalizing cloud infrastructure as code (e.g. Terraform, Serverless Framework, Pulumi)
- Proven experience in designing, deploying, and maintaining data pipelines that process and integrate text and image data, ETL processes, and data integration solutions in a production environment, and a proven track record of delivering high-quality, scalable, and reliable data solutions
- Strong knowledge of SQL and NoSQL databases as well as data warehousing concepts
- Knowledge of containerization technologies like Docker and Kubernetes and experience with deploying data pipelines in containerized environments
- Experience with version control systems like Git and familiarity with continuous integration and delivery (CI/CD) processes
- Familiarity with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Looker, Tableau, Power BI)
- Excellent problem-solving skills, with the ability to think critically and adapt to changing requirements
- Comfortable with ambiguity and taking on leadership roles in ambiguous tasks, demonstrating initiative and resilience in the face of challenges
- Detail-oriented, with strong organizational and project management skills, and the ability to manage multiple projects and priorities simultaneously
- Passion for learning and staying up-to-date with the latest data engineering technologies and trends
Nice to haves:
- Experience working in a fast-paced consulting environment, with a proven ability to handle multiple projects simultaneously, prioritize tasks, and meet deadlines
- Experience working with text and image data from social media platforms, such as Twitter, Reddit, or YouTube, and knowledge of social media analytics tools and methodologies
To be successful, the candidate must have a desire to deliver quality work for clients/brands, be a team player and demonstrate the ability to get the job done. You’ll need a serious interest of trends, best practices, technology and business applications on the Internet and within Methods+Mastery.
