Mikkel Dengsøe

Co-Founder @ SYNQ

Mikkel is a seasoned data leader and strategist with deep expertise in analytics engineering, data platforms, and modern data team practices.

About

Summary:

Mikkel is a seasoned data leader and a founder at SYNQ
Has built and run data teams in leading companies such as Monzo and Google
Mikkel is a respected speaker in events and meetups, sharing his expertise on running data teams and building data products

Experience

Co-Founder and Chief Evangelist at SYNQ
Head of Data @ Monzo Bank
Data Science Lead @ Google

Topics I write about

Connect with me

Featured articles

Hands-on with an MCP for data quality

How SYNQ's MCP, combined with the right metadata and context, can supercharge data quality workflows

August 26, 2025

Hundreds of actionable data quality guidelines

Building a collection of bite-sized guidelines for data teams – from testing to ownership and incident management best practices

August 18, 2025

Webinar: Testing smarter, not harder (AI edition)

Watch our AI-powered testing webinar with dbt Labs experts—learn where to place tests, avoid common pitfalls, and elevate data quality the smarter way.

August 5, 2025

July updates from SYNQ

What's new in SYNQ

July 31, 2025

Launching our Automated Testing & Monitor Advisor

We’ve evolved SYNQ’s AI capabilities to recommend tests and monitors to put you on par with industry-leading data teams

July 17, 2025

May 2025 updates from SYNQ

What's new in SYNQ in May 2025

June 1, 2025

Introducing Scout: Your always-on data SRE

Scout is our data quality agent that’s proactively monitoring, analysing, and resolving data quality issues on your behalf.

May 21, 2025

dbt vs SQLMesh: A Comparison For Modern Data Teams

This guide is designed to help data practitioners, engineers, and decision-makers thoroughly understand the key differences between dbt and SQLMesh.

April 30, 2025

March 2025 Updates from SYNQ

What's new in SYNQ in March 2025

April 3, 2025

How to Identify Your First Data Products

Taking the first steps to getting started with Data Products

March 12, 2025

Benchmark Your Data Team

What data from hundreds of top data teams tells us about team size, role distribution, data-to-engineer ratios, and salaries.

February 13, 2025

Building our SQLMesh Integration

Bridging model and table-level concepts to make the best-in-class data observability and SQLMesh integration

February 12, 2025

SYNQ & SQLMesh fireside chat

We’re excited to share a recent conversation between Petr Janda, founder of SYNQ, and Toby Mao, co‑founder and CTO of Tobiko (SQLMesh). In this fireside chat, they discuss our new integration with SQLMesh, why it matters for modern data workflows, and how it helps teams unify transformation and observability.

January 27, 2025

5 real-world data product use cases

Examples of how data products are used to solve real-world problems and drive meaningful business impact in B2B SaaS, eCommerce, logistics, and fintech

January 24, 2025

SQLMesh and SYNQ integration

Combine SQLMesh DataOps workflows with SYNQ’s Data Product Observability layer to deliver reliable data products

January 7, 2025

SYNQ’s 2024 Highlights

Reflecting on 2024, SYNQ introduced the Data Product Observability Workflow, enhancing data reliability through strategic testing, ownership activation, and quality metrics. Key developments include the launch of Data Products for streamlined monitoring and SLA tracking, advanced incident management features, and comprehensive data quality analytics. These innovations have empowered enterprises like IAG and Aiven to optimize their data operations effectively.

December 20, 2024

Supercharging data quality: Using a data reliability platform alongside dbt

How and when to extend dbt with a data reliability platform, and key considerations for vendor selection

October 21, 2024

Learnings from running hundreds of data incidents at SYNQ

How treating issues and incidents differently has driven accountability and a trace of systemic issues

August 26, 2024

How top data teams are structured

A deep dive into the ratio of data roles across insight, data engineering, and machine learning

July 26, 2024

How data observability fits into the different stages in the data pipeline

Explore how data observability integrates into each stage of the data pipeline, from source systems to analytics, enhancing data quality and reliability.

June 28, 2024

High-impact data governance teams

How to drive impact, where to focus, and what skills are required to succeed in the best data governance teams

May 30, 2024

ML & Gen AI for data teams

Building reliability by design for classical ML use cases and Gen AI

April 25, 2024

The cost of data incidents

A toolset for determining if a data incident is a $1,000 or $100,000 problem

March 4, 2024

Data ownership: A practical guide

A toolkit for defining and activating ownership across the data team, upstream teams, and business stakeholders

February 12, 2024

Measuring data quality: bringing theory into practice

Practical steps for measuring and actioning data quality

January 17, 2024

LendInvest webinar

Learnings from bringing ownership of data quality across the business

January 3, 2024

2023 recap

A year of growth, learning, and shipping

December 22, 2023

Building reliable machine learning models in the data warehouse

Combining dbt tests and anomaly monitors to proactively detect data quality issues on sources, features, and predictions

November 20, 2023

Building reliable data in fintech

Data reliability challenges fintech companies face with reconciliation, automated decisioning, regulation, and customer experience

October 19, 2023

Anomaly monitors and dbt tests to ensure the quality of critical pipelines

How to build reliable data pipelines by combining domain knowledge and automated data checks

August 25, 2023

The importance of data quality for automated customer engagement

How to improve the ROI of your marketing campaigns by reducing upstream data quality issues

July 21, 2023

The hidden cost of data quality issues on the return of ad spend

How leading companies drive value-driven ad spend allocation based on customer lifetime value and overcome costly data issues

July 5, 2023

How to identify your business-critical data

Practical steps to identifying business-critical data models and dashboards and drive confidence in your data

June 11, 2023

Activating ownership with data contracts in dbt

How to use data contracts, tests and Synq to enforce quality and activate ownership between producers, consumers and data teams

June 4, 2023

Untaming the spaghetti lineage

Why data lineage workflows break with scale and how to fix it

May 11, 2023

The struggles scaling data teams face

How asset sprawl in large data teams makes onboarding, development, monitoring and self-serve harder

May 4, 2023

Data and product to engineer ratio at 50 tech scaleups

What the number of data and product people relative to engineers can tell us about how top tech scaleups operate

April 13, 2023

Incident management for data teams

Practical steps for managing incidents in data teams for faster resolution, better transparency and less hassle

April 6, 2023

Data alerts are hard

The difficulty of building alerting workflows fit for scale

March 20, 2023

Analytics engineering workflows with dbt and Synq

Four improvements to your dbt workflows to build reliable data for scaling data teams

March 1, 2023

Europe data salary benchmark 2023

A pay benchmark for data analysts, data scientists, analytics engineers and data engineers across hundreds of companies

February 16, 2023

The complete guide to building reliable data with dbt tests

10 practical steps from top data teams

February 7, 2023

Designing severity levels for data issues

Things to consider when setting severity levels, how to act based on different severity levels and simple steps to getting started

January 20, 2023

Defining ownership and making it actionable

What to consider before defining ownership, how to manage ownership of upstream and downstream teams and a few simple steps to getting started

January 15, 2023

The unique challenges faced by fintech data teams

Fintech startups have multiple times the amount of critical metrics and data systems making the stakes higher than anywhere else.

January 12, 2023

Data team as % of workforce: A deep dive into 100 tech scaleups

What’s the right ratio of data roles in scaleups and why it should probably be higher than you think.

January 10, 2023