Senior Manager, Data Engineering

About Dashlane

Dashlane's mission is to make security simple for millions of organizations and their people. We empower businesses of every size to protect company and employee data while helping everyone easily log in to the accounts they need—anytime, anywhere. Over 17 million users and 20,000 businesses in 180 countries use Dashlane for a faster, simpler, and more secure internet.

Our global team is united by a strong sense of community and passion for improving the digital experience of our users. Learn more about how we work, how we hire, and the benefits of being a Dashlaner in our Life at Dashlane page.

About the role:

At Dashlane we see data as a true and reliable asset: data drives decisions based on timely insights and all teams are empowered to use data in their daily work. We are hiring a Senior Manager for Data Engineering to join our team, manage and mentor a growing team of 3+ data engineers. Enable our internal data users through building reliable, relevant, findable, and understandable data pipelines and models.

You will play a pivotal role of managing data at rest and in motion along with governance controls empowering  our business & technical users with trusted, timely and actionable data . You will be responsible for bringing robust, efficient, and integrated data models to life. You are expected to roll up your sleeves and deep dive into development on need basis. You should speak the language of business teams and technical teams, able to translate data insights and analysis needs into models. 

Location:
You will be based in Lisbon, with English as your working language. We offer a hybrid work arrangement, with Tuesday being the company day, where we all collaborate in the office and have a company-sponsored meal, a department day for team bonding (will be Thursday for your department), and a third day at your choice. We offer relocation support (national and international).

About our stack:

• Programming language: Python
• Data Platform: AWS [ S3, EC2, ECS, Lambda, Kinesis, Glue & DMS],  MySQL on RDS, Redis
• ETL and ELT Tools: Airbyte and Hightouch
• Data Modeling & Orchestration : DBT and Airflow
• Release management and CI/CD: Gitlab
• BI Tools: Tableau and Looker
• Infrastructure provisioning and management: Terraform & Ansible
• Logging and monitoring: ELK (ElasticSearch, Logstash, Kibana) & AWS Cloudwatch
• Incident management: PagerDuty
• Documentation and collaboration tooling: Confluence, Gitlab &  Slack

At Dashlane you will:

• Collaborate with data team members and data stakeholders to provide thought leadership  on how to leverage data infrastructure in analytical & operational context.
• Maintain and scale exiting data platform and architecture serving Dashlane business functions .
• Establish best practices for data engineering and management aligning with CTO office guidelines and framework requirements.
• Define and evolve data architecture adapting to changing business needs aligning with industry trends and best practices.
• Establish and enforce data quality standards and data governance practices.
• Define data operational excellence framework collaborating with  technology & business stakeholders. 
• Partner with analytics team and data stewards on maintaining analytics datastore for operational data driven decisions. 
• Build trust in all interactions and with our data platform by balancing strong interpersonal skills with a strong commitment to maintaining high-quality outputs.
• Provide data modeling expertise through code reviews, pairing, and training to help deliver optimal, and scalable database designs and queries in AWS Redshift.
• Design, develop, and extend dbt models that support product and business decisions and data-driven innovation.
• Design and develop appropriate data quality tests in accordance with the existing data quality framework to ensure a high level of model quality and foster a culture of trust in data.
• Create and maintain models architecture and documentation.
• Assist data science team to build  MLops workflows and models for predictive modeling & analytics.

Requirements:

• 5+ years experience as a senior data engineer.
• 3+ years experience of managing a team of 4+ engineers.
• Demonstrated strength with hands on experience in design and development of data pipelines, data lakes and data warehouses.
• Experience applying software engineering best practices and guidelines to analytics code and data model development.
• Working knowledge of BI tools such as Tableau/Looker/Power BI.
• Positive and solution-oriented mindset.
• Comfortable on working in a highly agile, intensely iterative environment.
• Self-motivated and self-managing, with task organizational skills.
• Great communication: Regularly achieve consensus amongst technical and business teams.
• Demonstrated capacity to communicate complex business activities, technical requirements, and recommendations clearly and concisely.
• Ability to thrive in a distributed organization.
• Fluent in English: verbal and written.

Diversity, Equity, Inclusion and Belonging at Dashlane:

As a truly international company—founded in France and distributed across France, US and Portugal—Dashlane thrives off diverse perspectives. We value all aspects of diversity: gender identity, sexual orientation, ability, ethnic origin, social background, age, lifestyle, and more. We are committed to hiring a diverse community and fostering a culture where everyone is heard and belongs. See more about this here. 

Your interview experience: 

To know what to expect once you’ve sent your application, read about how we interview and hire at Dashlane. Feel free to browse our blog to find more information about our product and how we work.