Senior Data Engineer (Marketing)

Docker is a remote-first company with employees across Europe, APAC, and the Americas that simplifies the lives of developers making world-changing apps. We raised our Series C funding in March 2022 for $105M at a $2.1B valuation. We continued to see exponential revenue growth last year. Come join us for a whale of a journey! The Marketing Data Engineer is the data subject matter expert supporting the critical data foundation that enables marketing growth and retention campaigns as well as data science/analytics functions within the Growth Marketing organization. Responsibilities: - Works with business leaders and analysts across the organization to analyze and help define requirements, mine and analyze data, and integrate data from a variety of sources. - Creates and maintains data pipelines between multiple martech systems and databases (e.g., Snowflake, BigQuery) to ensure the marketing data lake is positioned for future success. - Create and maintain data modeling for audience segmentation, product recommendation, predictive scoring, and customer affinities. Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. - As a data steward, responsible for the management of detailed marketing data cataloging and data transformations of source data feeding the data lakes (Snowflake); ensures source data definitions are consistent across the organization and with industry standards. - Create and manage SQL code and Salesforce Marketo automations for campaign-specific needs, journey automations, CRM updates, and ingesting new data into databases. - Identify areas of improvement and implement efficiencies in the data ecosystem. - Responsible for resolving data discrepancies and irregularities with source data systems and marketing platforms/partners. - Helps maintain the ETL process and data modeling for future expansion. - Performs consistent data audits to continuously improve data reliability, quality, and efficiency. - Ensures all data security and governance principles are achieved and maintained. Key qualifications: - Strong proficiency in SQL and a scripting language (Python or R preferred). - Knowledge of data manipulation and analysis tools such as DBT, Atlan, SQL, Excel, and Google Analytics. - Typically requires 5+ years in building data pipelines. - In-depth knowledge and understanding of marketing data assets (first and third party). - Demonstrated experience in data engineering, data structures, data modeling, and data/platform integration. - Excellent communication, presentation, influencing, and reasoning skills. - Ability to clearly communicate complex concepts with both technical and non-technical stakeholders. - A thorough knowledge of data set taxonomies which include digital channel taxonomy and customer data taxonomy to create seamless nomenclature within data assets. - Knowledge of machine learning algorithms and techniques (optional but beneficial). What to expect in the first 30 days: - Get to know the teams, products, and customers. - Learn the data schema, martech architecture, and data pipelines. - Get acquainted with the Docker culture centered around humility, developer obsession, open collaboration, and bias for considered action. What to expect in the first 90 days: - Create a plan with stakeholders to build solid data management systems and reporting for their programs. - Drive insights and uncover optimization opportunities from currently available data. - Work closely with different teams to influence decisions on infrastructure and represent marketing and its needs. What to expect in the first year: - Support overall decision-making and have solid tools and models in place to enable effective and scalable growth and campaign operations. - Use advanced database management techniques to understand how to better capture personas behavior data and create account segments that will improve the understanding of current personas' behaviors. - Support the cultural changes to become a data-driven organization by enabling a wide variety of stakeholders to understand and use data in their decision making. Perks: - Freedom and flexibility; fit your work around your life. - Home office setup; we want you comfortable while you work. - 16 weeks of paid Parental leave. - Technology stipend equivalent to $100 net/month. - PTO plan that encourages you to take time to do the things you enjoy. - Quarterly, company-wide hackathons. - Training stipend for conferences, courses, and classes. - Equity; we are a growing start-up and want all employees to have a share in the success of the company. - Docker Swag. - Medical benefits, retirement and holidays vary by country. Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be. Due to the remote nature of this role, we are unable to provide visa sponsorship. #LI-REMOTE