APPLY is seeking a Senior Data Engineer to join our Data team. You will build and own data foundations on modern cloud data warehouses such as Snowflake using dbt-based ELT: from source audits and migration guidelines, through modelling (identity resolution, semantic and consumption layers), to activation pipelines into customer engagement platforms such as Braze. You will work closely with cross-functional teams, clients and third-party vendors to define data requirements, translate business needs into technical specifications, and produce clear, actionable recommendations.
The successful candidate will have a strong background in data engineering on the modern data stack and excellent communication skills to interact with stakeholders and clients. If you have a passion for technology, thrive in a dynamic environment, and possess strong client-facing communication skills, we want to hear from you.
RESPONSIBILITIES:
Work with internal disciplines, vendors, clients and stakeholders to define data requirements and the technology stack for projects.
Audit source systems (CRM and marketing platforms such as Salesforce and Sailthru) and define migration guidelines: what to migrate, in what structure and in what order, for execution by internal or third-party teams.
Translate business requirements into technical specifications including data streams, integrations, transformations, databases and data warehouses.
Design and build transformation layers in dbt on Snowflake, including identity resolution, semantic layer and consumption/reporting layers.
Build and maintain pipelines that activate data in customer engagement platforms (e.g., Braze).
Run discovery audits of digital products (apps, games, web) and produce data foundation recommendations.
Work in git-based workflows with code review, dbt tests and existing CI/CD processes for warehouse objects.
Define the data architecture framework, standards and principles, including modelling, metadata, security and reference data; analyze and optimize existing architectures and models for performance and cost.
Create a plan of activities required to populate new solutions with all current and historical data.
Implement data security and access controls to ensure compliance with company policies and regulation.
Document data sources, ELT/ETL processes, data dictionaries and metadata to facilitate data discovery; maintain data lineage and data flow documentation.
Research, evaluate and recommend new technologies, and develop best practices for data management, security and privacy.
REQUIREMENTS:
A Bachelor's degree in Computer Science, Information Systems, or a related field.
At least 5 years of experience in data engineering or related fields.
Expert-level SQL and strong experience in ELT/ETL and cloud data warehousing, with hands-on Snowflake experience.
Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows (branching, code review, CI/CD).
Proven experience in data modelling (dimensional and semantic layers) and analysis techniques.
Experience with customer data modelling and identity resolution across CRM, marketing and product sources.
Experience integrating data with customer engagement platforms (Braze, Salesforce Marketing Cloud, Sailthru or similar).
Experience planning data migrations between platforms: source audit, mapping, target structure definition and historical backfill.
Working knowledge of Python for data tooling and automation.
Working knowledge of at least one major cloud platform (AWS or GCP) and its data services.
Demonstrated ability to troubleshoot data issues and develop effective solutions.
Comfortable producing written guidelines and recommendations for client and third-party teams.
Understanding of data privacy and security best practices.
Excellent communication and problem-solving skills.
Fluent English.
Snowflake (SnowPro) or dbt certification; cloud certifications welcome.
Spark/PySpark.
Docker and Kubernetes.
Experience with consumer or digital-product data (apps, games, subscriptions).
Nice to Have
Skills Required
- Bachelor's degree in Computer Science, Information Systems, or a related field
- At least 5 years of experience in data engineering or related fields
- Expert-level SQL experience
- Strong experience with ELT/ETL and cloud data warehousing
- Hands-on experience with Snowflake
- Strong hands-on experience with dbt, including modeling, tests, documentation, and macros
- Experience with Git-based workflows, branching, code review, and CI/CD
- Experience with dimensional and semantic data modeling and analysis techniques
- Experience with customer data modeling and identity resolution across CRM, marketing, and product sources
- Experience integrating data with customer engagement platforms such as Braze, Salesforce Marketing Cloud, or Sailthru
- Experience planning data migrations, including source audits, mapping, target structure definition, and historical backfill
- Working knowledge of Python for data tooling and automation
- Working knowledge of AWS or GCP and its data services
- Ability to troubleshoot data issues and develop effective solutions
- Ability to produce written guidelines and recommendations for client and third-party teams
- Understanding of data privacy and security best practices
- Excellent communication and problem-solving skills
- Fluent English
- Snowflake SnowPro, dbt, or cloud certification
- Experience with Spark or PySpark
- Experience with Docker and Kubernetes
- Experience with consumer or digital-product data, including apps, games, or subscriptions
What We Do
Digital to our core, we are purpose built to transform possibilities for people. We solve complex problems with well-executed solutions tailor-made for continuous growth — we’re ambitious and our clients are too. We work with well-funded start-ups, global brands, and Fortune 1000 companies spanning industries and audiences, including EA, Moderna, League Health, and Realtor.com.
