About Us:
A global SaaS leader for seamless digital document workflows, Nitro offers a suite of solutions for PDF, eSigning, identity verification and analytics supported by a best-in-class customer success and change management team. With more than 3 million licensed users and 13,000+ business customers across 157 countries, we serve 67% of the Fortune 500.
How We Work:
We aim to create an environment where talented individuals are empowered to excel. How we collaborate, innovate, and engage with one another is important to us. Our work is driven by 5 key principles:
- One team, One mission
Our collective dedication to Nitro's mission defines us. Together, we are building an environment where everyone feels like a valued part of something bigger than themselves. - Own it
We take full ownership of our actions and decisions. We empower one another to lead with confidence, creativity, and a solutions-focused mindset. - Accountable to our customers
We are dedicated to our customers and take our commitments seriously. We do what we say we are going to do. - Excellence in execution
Driven by passion and precision, we exemplify excellence in our delivery with innovative, top-quality results. - Be bold, fail fast, learn faster
We learn as we grow, dare to try, and bravely question. We are not chasing perfection but forever iterating towards it.
These guiding values shape our approach to work, fostering a culture where everyone is inspired to contribute their best.
Why Nitro Engineering:
Engineering is a critical function at Nitro, developing the products and services at the heart and soul of our business today, and helping us realize our vision of smarter documents in the future. We have an incredibly talented and diverse Engineering team that cares, with a strong culture that believes in building the right things and building them the right way.
The Role :
We're looking for a Senior Analytics Engineer to join our Data Science & Analytics team in Porto. You will leverage your expertise in both Data Engineering and Data Science to design and build robust data pipelines, manage ETL workflows, and enable efficient data accessibility across the organization. In addition to engineering capabilities, you will apply your analytical skills to perform quick data analyses, deliver actionable insights, and support data-driven decision-making. This role requires a strong technical foundation to implement scalable data solutions as well as a data science mindset to build predictive models, explore data trends, and address complex business challenges.
What you'll be doing :
- Delivering actionable business insights through in-depth analysis
- Performing analysing and building data models to optimise sales and marketing predictions and activities
- Partnering with Data Engineers and Product teams to define and maintain robust data structures that support seamless analysis and product instrumentation strategies.
- Working with massive data sets, you will build strong domain knowledge and help identify gaps in our data
- Designing, developing, and operating data pipelines to provide high quality datasets to internal and external customers.
- Working with other engineering teams to design product instrumentation strategies
- Using state of the art, cloud based technologies primarily on AWS
- Helping to establish best practice in data engineering
- Mentoring more junior team members
- Identifying how to use AI to drive our vision of making documents smarter
What we're looking for:
- 5+ years of experience in data/software engineering
- Familiarity with Python and Scala
- Strong SQL skills and experience extracting datasets from disparate sources
- A strong background in statistical analysis and data mining
- Experience working with open problem statements and mapping business problems into data analysis opportunities
- Experience with analysis and visualization tools (such as Jupyter notebooks, Zeppelin, Superset, QuickSight, Tableau, etc.)
- Enthusiasm, passion, strong collaboration skills and a desire to explore large datasets
Traits that will distinguish the ultimate candidate:
- Independence and autonomy as regard data modelling and working beside and within Engineering environments
- Experience with version control and data modelling environments (e.g. DBT)
- Experience with large-scale data processing frameworks (e.g. Spark, EMR, Hadoop) and data pipelines (e.g. AWS data pipelines)
- Experience with event driven and streaming architectures (e.g. Kafka, Spark-Streaming, Flink, Akka Streams)
- Production experience with a functional programming language (particularly Scala, but also Clojure, Haskell, Erlang, …)
- Experience managing a data warehouse (ideally Snowflake)
- Working knowledge of a cloud environment (ideally AWS)
- Experience of configuration as code, i.e., Terraform
- Experience in Micro-service architectures, RESTful services and integrating with third party services.
- Working knowledge of containers and container orchestration (Kubernetes) and Kubernetes layered software, e.g., ArgoCD
- A DevOps mindset
Why Nitro?
Along with our regular benefits and programs (including health, dental, vision, and retirement as standard), we are also very proud to offer a few additional initiatives to future Nitronauts:
Hybrid Work
Our team embraces the hybrid work model, appreciating its blend of flexibility and structure. We combine three days of in-person collaboration at our global offices in Toronto, Dublin, Antwerp, Porto, and Melbourne with the convenience of two days of remote work each week.
Benefits:
Nitro provides all employees with a comprehensive benefits package that includes health insurance, dental and vision coverage, and wellness perks. We also offer pension/401k matching, along with many other country-specific benefits.
Nitro strongly encourages applications from everyone regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status. We provide an accessible candidate experience and invite you to request any accommodations or adjustments throughout the interview process and beyond.
#LI_EC1 #LI-Hybrid
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