3-5+ years of experience in data engineering and data architecture., Proficiency in SQL, dbt, and Python., Experience with building and optimizing data pipelines and models., Knowledge of data monitoring, automation, and observability best practices..
Key responsibilities:
Build and optimize data pipelines from multiple sources.
Design and implement data models for product and customer analytics.
Automate data workflows and establish monitoring systems.
Communicate technical data solutions to non-technical stakeholders.
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Inclusion Cloud is the leading global independent tech outsourcing services innovator, founded in 2007 with over 200 professionals from more than 15 countries.
We help organizations access the best enterprise IT talent and software solutions globally.
With an expanding client base including companies like Roche, GoodYear, Oracle, AES, Gilbarco and more, Inclusion Cloud is trusted by world-class brands serviced by teams across more than 20 cities and headquartered in Washington DC and Dallas (Texas), United States.
Inclusion empowers organizations to engineer innovative products and solutions to quickly adapt to changing circumstances, improve their efficiency, and stay ahead in their markets.
Perform Product data engineering in partnership with Software Engineering to build new Product features and enhancements.
Build Product and Customer Analytic Data Architecture: Build the data infrastructure necessary to analyze & support Product strategy.
Build and Optimize Data Pipelines: Design, build, and deploy data pipelines from multiple source systems; refactor existing pipelines for performance.
Perform Data Modeling: Implement data modeling best practices in dbt.
Automate and Monitor Data Processes: Document data workflows, automate pipelines, and establish observability and monitoring to ensure availability of analytic & Product data.
Present and Communicate Technical Solutions: Clearly communicate technical topics and data solutions to non-technical stakeholders to achieve buy-in.
Required Skills
3-5+ years of experience in data engineering and data architecture.
Experience working with Software Engineering and DevOps as part of the Product development lifecycle.
Demonstrated experience building data models for capturing software application telemetry and website traffic for Product usage & site visitor analytics.
Demonstrated experience building data models for capturing billing and subscriber transactions to support revenue and retention analytics.
Expertise in SQL, dbt, Python, batch & streaming processing, change data capture, orchestration, scheduling, and data migration best practices - experience with Postgres, Snowflake, Airflow, and Dagster preferred.
Hands-on expertise designing data quality & pipeline observation, monitoring, and alerting best practices.
Knowledge of or experience with advertising/adtech business models preferred.
Ability to integrate analytic data pipelines into Business Intelligence tools - Looker preferred.
Knowledge of or experience with GitHub for code management.
Required profile
Experience
Level of experience:Mid-level (2-5 years)
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.