Senior Engineer II co - owning the technical roadmap for data solutions at Instacart. Building scalable data - intensive systems and mentoring engineers.
About the role
- Analytics Engineer responsible for designing, building, and maintaining scalable data pipelines. Contributing to AI-enriched data infrastructure for revenue-focused initiatives across various teams at Meltwater.
Responsibilities
- Design, build, and maintain scalable dbt models on Snowflake/Databricks/Big Query that transform raw source data into reliable, well-documented datasets for analytics and reporting.
- Build and orchestrate Airflow DAGs that coordinate dbt runs, Snowpark Container jobs, and external task sensors across 20+ source systems.
- Integrate data from Salesforce, Gong, Intercom, Google Ads, Zoom, Satismeter, Workday, Gainsight, Kantata, Jira, and other external APIs into a unified revenue data model.
- Develop incremental, merge-based models with appropriate unique keys, schema-change handling, and date-window filtering for cost-efficient refreshes.
- Apply Snowflake Cortex AI functions (COMPLETE, SENTIMENT, TRANSLATE, SPLIT_TEXT_RECURSIVE_CHARACTER) to enrich text-heavy datasets such as call transcripts, emails, and survey responses, and produce vector-ready chunks for Cortex Search.
- Collaborate on AI/ML pipelines that combine dbt transformations with Snowpark Container Services jobs (e.g., PII redaction) to produce safe, enriched 360° views of customer interactions.
- Optimize warehouse usage, query patterns, and model materializations for performance, scalability, and cost — including query tagging for cost attribution and audit.
- Establish and enforce data quality standards through dbt tests (uniqueness, not-null, referential integrity), source freshness checks, and Airflow short-circuit validators.
- Implement data governance best practices — RBAC-driven schema promotion, masking/PII handling, lineage documentation, and compliant access patterns across source and prod.
- Work closely with Revenue Operations, FP&A, Sales, CS, and Business Applications teams to translate business questions into well-structured datasets and semantic models.
- Support the deployment of data-driven models and algorithms (AI tagging for use cases, churn-risk signals, competitor mentions, sentiment scoring, semantic search over conversations) in close collaboration with stakeholders.
- Contribute to shared dbt macros, testing frameworks, and CI/CD practices (SQLFluff linting, Slack-based alerting).
Requirements
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- 2-4 years of experience in data engineering, ETL development, and database management.
- Proficiency in SQL and Python, with experience using ETL and reverse ETL tools like Fivetran, Census, Hightouch, and DBT.
- Familiarity with data visualization tools (Tableau, Power BI, Looker, etc)
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies.
- Strong problem-solving skills and attention to detail.
- Effective communication skills to collaborate with cross-functional teams.
- Preferred experience with data warehousing solutions such as Snowflake and Databricks.
Benefits
- Flexible paid time off that allows you to have an enhanced work-life balance
- Excellent medical, dental, and vision options
- Complimentary CalmApp subscription for you and your loved ones, because mental wellness matters.
- Energetic work environment with a hybrid work style, providing the balance you need.
- Thrive within our inclusive community and seize ongoing professional development opportunities to elevate your career.
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