Senior Data Engineer

Alembic is pioneering a revolution in marketing, proving the true ROI of marketing activities. The Alembic Marketing Intelligence Platform applies sophisticated algorithms and AI models to finally solve this long-standing problem. When you join the Alembic team, you’ll help build the tools that provide unprecedented visibility into how marketing drives revenue, helping a growing list of Fortune 500 companies make more confident, data-driven decisions.

As a Senior Data Engineer at Alembic, you will be at the core of our data platform, building scalable and reliable data pipelines, optimizing storage solutions, and enabling real-time and batch analytics. You will work closely with data scientists, software engineers, and product leaders to design and implement robust data architectures.

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  Design, develop, and maintain scalable ETL pipelines that ingest, process, and transform large volumes of structured and unstructured data.

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  Optimize data storage solutions using modern data lakehouse architectures and best practices for cost, performance, and reliability.

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  Collaborate with data scientists and engineers to integrate machine learning models and analytical workloads into production environments.

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  Ensure data integrity, quality, and security by implementing monitoring, alerting, and governance best practices.

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  Work with cloud-based data warehouses and distributed data processing frameworks.

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  Continuously evaluate and implement new technologies to improve data infrastructure and operational efficiency.

• 10+ years of experience in data engineering, software engineering, or a related field.

• Strong expertise in SQL and Python for data processing.

• Experience with modern data warehousing and lakehouse solutions (i.e. Iceberg or similar).

• Proficiency in working with distributed systems and big data technologies (Apache Spark, Hadoop, Kafka, Flink).

• Hands-on experience with cloud platforms (AWS, GCP, Azure) and related data services.

• Deep understanding of data modeling, database design, and performance optimization.

• Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, CloudFormation) for data pipelines.

• Strong problem-solving skills, with a passion for building reliable, scalable, and maintainable data systems.

• Excellent communication skills and the ability to collaborate in a cross-functional team.

• Experience with Graph Databases, NoSQL, or Time-Series Databases.

• Familiarity with data privacy, governance, and compliance (GDPR, HIPAA, SOC 2).

• Experience with machine learning pipelines and MLOps.