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Website: higherlogic.com
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Higher Logic is seeking an Associate Data Solutions Engineer to power our data strategy and analytics capabilities. This full-time position, based in the United States, offers an exciting opportunity to own data infrastructure that serves over 3,000 customers globally, reporting directly to our Chief Data Officer. Role Overview As an Associate Data Solutions Engineer at Higher Logic, you'll architect and deploy the systems that transform raw information into strategic insights. You'll manage the complete lifecycle of data—from ingestion and transformation through delivery to analytics consumers—working with both structured databases and unstructured sources. Your work directly powers decision-making across product, operations, and customer success teams, and positions Higher Logic to scale AI-driven capabilities into our platform and customer solutions. Core Duties Design and deploy reliable ETL and ELT pipelines that move data at scale from source systems into our centralized data warehouse environment. Model data architectures that support real-time dashboards, self-service analytics, and automated operational workflows. Write maintainable SQL and Python code to process, validate, and reshape data into formats ready for consumption by analysts and systems. Partner with product, analytics, and engineering teams to capture data requirements and translate them into technical solutions. Establish performance baselines and monitoring protocols to guarantee data quality, delivery speed, and accuracy across all pipelines. Build orchestration layers that activate AI models and workflows in response to business events and rule-based conditions. Lead by example in data governance, documenting schema design patterns, access policies, and security best practices. Champion adoption of modern data tools and frameworks—such as DBT, Iceberg, and Databricks—to keep our stack competitive and efficient. Identify gaps in data infrastructure and propose solutions aligned with business priorities and enterprise scalability. Requirements Demonstrated expertise in SQL and Python for data extraction, transformation, and loading workflows. Hands-on experience with at least one modern data warehouse platform, such as Databricks, Snowflake, BigQuery, or similar. Exposure to contemporary data stack tools including transformation frameworks (DBT), table formats (Iceberg, Delta Lake), or orchestration platforms. Proven ability to work with both relational data and semi-structured sources (APIs, logs, JSON, Parquet). Understanding of data quality verification, observability, and pipeline monitoring…
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