Acquia

Senior Software Engineer, SQL, Snowflake, Data Modeling, Cloud Data Platforms

Acquia

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

Senior

Tech Stack

AirflowAWSAzureCloudETLGoogle Cloud PlatformKafkaPythonSQL

About the role

  • Design and build scalable data pipelines using Dagster for orchestration and Snowflake for data warehousing
  • Develop and optimize complex data models and transformations to support real-time analytics and AI/ML initiatives
  • Build metadata-driven, reusable data solutions that enable self-service analytics across the organization
  • Implement AI-powered data quality monitoring, anomaly detection, and automated data validation frameworks
  • Partner with Data Scientists and ML Engineers to enable efficient model training and inference workflows
  • Optimize query performance and cost efficiency across multi-petabyte data workloads in Snowflake
  • Build robust data governance frameworks including lineage tracking, data cataloging, and access controls
  • Implement event-driven data architectures supporting real-time customer experience optimization
  • Collaborate with Product and Engineering teams to instrument applications for comprehensive data collection
  • Mentor junior engineers on data engineering best practices and modern data stack technologies

Requirements

  • 5+ years of experience in data engineering roles with focus on large-scale data processing
  • Expert-level proficiency in Python for data pipeline development and automation
  • Strong SQL skills with experience in query optimization and performance tuning
  • Strong hands-on experience with Snowflake including performance optimization, security, and cost management (must-have)
  • Proven experience with Dagster or similar workflow orchestration tools (Airflow, Prefect)
  • Deep understanding of data modeling, ETL/ELT patterns, and dimensional modeling techniques
  • Experience with streaming data technologies (Kafka, Kinesis, Pub/Sub) and real-time processing
  • Experience with cloud data platforms (AWS, GCP, Azure) and their native data services
  • Knowledge of data governance tools and practices (data cataloging, lineage, quality monitoring)
  • Familiarity with version control (Git) and CI/CD practices for data pipelines
  • Interest in AI/ML applications including feature engineering, model serving, and MLOps workflows.
Benefits
  • competitive healthcare coverage
  • wellness programs
  • take it when you need it time off
  • parental leave
  • recognition programs

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
PythonSQLSnowflakeDagsterETLELTdata modelingstreaming data technologiescloud data platformsdata governance
Soft skills
mentoringcollaborationcommunication