We are looking for a Lead DWH Engineer to manage and grow the Data Engineering team while ensuring the delivery and quality of our data warehouse. You will own team processes, drive execution, and act as the bridge between engineering, product, and business stakeholders.

Responsibilities

Lead and manage the Data Engineering team: task prioritization, code reviews, 1-on-1s, hiring, and professional development of team members.
Own the delivery of DWH development: sprint planning, backlog management, and ensuring timely execution of data initiatives.
Communicate data requirements and dependencies with Integration and Data Science teams — ensure new data source integrations and partner data feeds are aligned with DWH standards and timelines.
Collaborate with CSM, product, and marketing analytics teams to translate business requirements into engineering tasks and delivery plans.
Maintain and evolve the transformation layer — ensure code quality, modularity, testing, and documentation standards across the project.
Participate in strategic decisions on DWH expansion: new source integration, schema evolution, and performance tuning.
Monitor and optimize the MPP Database environment: cost control, query performance.
Establish and enforce engineering best practices within the team: CI/CD, version control, testing, and code review standards.
Proactively identify bottlenecks, technical debt, and opportunities for improvement across the data platform.

Requirements

5+ years of experience in data engineering / data warehousing, with at least 2 years in a lead or engineering management role.
Experience managing a data engineering team: task planning, performance reviews, mentoring, and hiring.
Strong cross-functional communication skills — ability to define and negotiate data requirements with Integration and CSM teams, aligning on data source availability, SLAs, and delivery timelines.
Hands-on expertise with Data Vault methodology (raw vault, business vault, information marts).
Production experience with dbt — advanced knowledge of macros, incremental models, tests, and packages.
Solid knowledge of Redshift, BigQuery, Snowflake, etc.: performance optimization and cost management.
Understanding of S3-based data lake patterns and data ingestion strategies (batch and near-real-time).
Experience with Airflow or similar orchestration tools.
Domain expertise in mobile/web Performance Marketing — clear understanding of subscription-based monetization, ad revenue models, and one-time payment flows.
Experience working with attribution data, SKAN, MMP integrations (AppsFlyer, Adjust, etc.), ad network APIs, and campaign-level granularity.
Strong SQL skills and ability to reason about complex analytical queries.
Experience with CI/CD for data pipelines and version-controlled analytics workflows (Git).
Excellent communication skills — ability to articulate technical decisions and trade-offs to both technical and non-technical stakeholders.
English level: B1.

Nice to Have

Familiarity with BI/analytics layer (Looker, Tableau, Metabase) and how DWH design impacts downstream reporting.
Knowledge of data privacy frameworks relevant to mobile marketing (GDPR, ATT, CCPA).
Experience with reverse ETL or operational analytics patterns.
Background in Python for data pipeline tooling and automation.
Exposure to real-time/streaming architectures (Kafka, Kinesis).
Contributions to the dbt or Data Vault community (packages, blog posts, talks).

What We Offer

Competitive salary + performance bonus.
Fully remote with flexible working hours.
Home office stipend and learning & development budget.
25 days holiday (+ local public holidays).
Regular team offsites and a culture that actually lives its values.

Campaignswell is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive team. If you're passionate about helping brands grow through smarter data and love collaborating across disciplines to deliver impact, we’d love to hear from you!

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