Data Engineering Consulting
I design and build data pipelines, cloud data platforms, and analytics engineering solutions that give teams the data they need — on time, at scale, and without the toil.
End-to-end data engineering — from raw ingestion to analytics-ready models.
Batch and streaming pipelines built with Airflow, dbt, Spark, and Kafka. Idempotent, observable, and easy for your team to maintain.
Architecture and implementation on AWS (Glue, Redshift, Lake Formation, Athena), Snowflake, and BigQuery — right-sized for your workload and budget.
Dimensional models, data vault, and analytics-layer transformations with dbt. Clean, documented, tested models your analysts can trust.
Lift legacy SSIS, Informatica, or custom scripts to modern ELT patterns. Less fragility, faster iteration, lower ops overhead.
Semantic layer design, metric definitions, and self-serve analytics foundations. Bridges the gap between raw data and BI tools your stakeholders actually use.
Automated data quality tests, lineage documentation, access control patterns, and HIPAA/compliance-ready data architectures.
Tools I use daily — not checkbox certifications.
I'm Scott Merklinger, an independent data engineering consultant with experience designing and delivering data infrastructure across healthcare, enterprise SaaS, and cloud-native startups.
I work with engineering teams and data leaders who need to move fast — building pipelines that are correct, observable, and maintainable by the people who inherit them. No bloat, no over-engineered abstraction layers.
When I'm not building pipelines I'm thinking about AI-augmented data workflows, agentic automation, and the next generation of data tooling.
Work with meTell me about your data challenge. I'll respond within one business day.