What is the job?As a Senior Data Engineer, you will play a critical role in designing, building, and optimizing scalable data pipelines and architectures that support advanced analytics, machine learning, and business intelligence initiatives.
You will own the full path data takes through the platform: ingesting from source databases, third-party APIs, and vendor file feeds; landing and transforming it into governed warehouse models; and provisioning the underlying warehouse infrastructure as code. The platform spans on-premises and cloud source systems across a large, multi-domain estate (hundreds of source tables and transformation models) supporting business areas such as point-of-sale/box-office, loyalty, payments, and digital analytics.
You will collaborate closely with data scientists, analysts, and business stakeholders to ensure data is accessible, reliable, and actionable. This role requires a deep understanding of data engineering best practices, cloud platforms, and modern data stack technologies.
What will you be doing? - Design, develop, and maintain robust, scalable, and efficient data pipelines
- Build and maintain SQL-based transformation models in a version-controlled analytics engineering framework (e.g. dbt), including incremental processing strategies and macros
- Architect and implement robust data models, dimensional models, and aggregate models.
- Provision and maintain warehouse infrastructure - databases, schemas, roles, and grants - as code
- Collaborate with enterprise business units to understand data requirements
- Optimize data systems for performance, scalability, and cost-efficiency, including compute sizing and cost/credit budget monitoring
- Ensure data quality and integrity through automated testing, source-to-target reconciliation, freshness monitoring, and documentation
- Implement and maintain performant CI/CD pipelines for data workflows
- Implement and maintain data governance and security controls, including role-based access, column-level data masking, and support for privacy/compliance requests
- Migrate and modernize legacy data and reporting systems onto current platform capabilities
- Mentor junior engineers, review peers' code, and contribute to team knowledge sharing and best practices
- Create comprehensive documentation of existing and planned data processes
About you - Bachelor's degree or above in Computer Science, Information Systems, or related science field, or equivalent practical experience
- 5+ years of experience as a Data Architect, Data Engineer, Analytics Engineer, or similar role
- Strong SQL skills and experience integrating relational source databases, on-premises and/or cloud-hosted (e.g. SQL Server, MySQL/Amazon RDS)
- Hands-on experience with a cloud data warehouse platform (e.g. Snowflake)
- Experience ingesting from non-relational sources - REST APIs, cloud analytics exports (e.g. BigQuery/GA4), and vendor file feeds (e.g. SFTP, fixed-width/CSV)
- Proficiency in data modeling, ETL/ELT processes, and data warehousing solutions
- Experience with a general-purpose programming language and associated testing/code-quality practices (e.g. Python)
- Experience with a SQL transformation/analytics engineering framework (e.g. dbt)
- Experience with Python-based ingestion frameworks or managed connectors (e.g. dlt, Fivetran, Airbyte)
- Hands-on experience with cloud platforms (e.g. Azure - Blob/ADLS, Data Factory, Key Vault, Entra)
- Hands-on experience with orchestration tools (e.g. Airflow, Prefect)
- Hands-on experience with infrastructure as code tools (e.g. Terraform)
- Experience with version control and CI/CD (e.g. GitHub Actions, Bitbucket Pipelines)
- Implementation experience with data governance, security, and compliance standards (e.g. RBAC, column-level masking, PII handling)
- Excellent analytical, problem-solving, and written communication skills - able to document decisions and trade-offs clearly for technical and non-technical audiences
- Ability to work cross-functionally with technical and non-technical teams
Preferred Criteria:
- Experience with hybrid connectivity between cloud and on-premises networks (e.g. VPN/VNet, private endpoints, DNS forwarding)
- Experience with CDP, reverse-ETL, or audience activation tooling (e.g. RudderStack, Braze, Google Ads Customer Match)
- Experience with BI platform security models (e.g. Power BI row-level security, Sigma)
- Familiarity with data catalog and lineage tooling (e.g. DataHub)
- Experience migrating off legacy ETL/BI stacks (e.g. SSIS, SSAS, SQL Server Agent)
Our Benefits - Discretionary annual bonus
- Free movie passes and discounted concessions at any Regal location
- Paid vacation time and sick leave to support a healthy work-life balance
- Eligibility to participate in our 401(k) retirement plan with company match after age 21 and one month of service
- Summer half-day Fridays during the summer season
- Medical and prescription coverage, with company contributions toward the cost
- Company-paid life insurance and disability insurance at no cost to employees
- Dental, vision, and supplemental life insurance options available for employees and their dependents
- Additional coverage options including accident, critical illness, and hospital indemnity insurance
