Senior Data Engineer/Scientist - Search

Project Description

PwC established New Ventures to invest in new business models that leverage our knowledge and build solutions for the growing digital market.

New Ventures identifies, develops, and commercializes technology-enabled solutions that deliver PwC value, knowledge, and experience to our clients. Each new solution focuses on data-driven platforms or other IP-based solutions that leverage emerging technologies and new business models. Through the process of building new solutions, we foster a culture of innovation within the Firm, extend brand relevance in the market, and generate new revenue.

Position/Program Requirements

Minimum Year(s) of Experience: 5 in software development.

Minimum Degree Required: Bachelor's degree in Engineering, Computer Science or related field.

Role responsibilities

Provide architecture guidance based on use cases, business requirements, availability, data model, and query requirements

Design and implement solutions related to Elasticsearch topics, such as relevancy, boosting, function scores, data modeling, percolator, or other Elasticsearch platform requirements.

Support developers to successfully integrate with Site Search or App Search APIs. This can include assistance modifying the search experience and implementing search logic.

Required skills:

Demonstrates intimate knowledge and/or a proven record of success in modern software engineering approaches, technologies, and tools:

- Cloud-ready architectures utilizing infrastructure and platform cloud services for AWS, GCP, or Azure

- Event-driven and microservices architectures

- Big Data / Analytics / AI tools 

- Rapid-prototyping workflows & development tools 

- Databases: relational (mySQL, postgres), noSQL (mongo, neo4j, firebase)

- Containers: Docker, Kubernetes

- ELK stack

Preferred skills: 

Demonstrates extensive abilities and/or a proven record of success in technical lead roles involving the following areas:

- Working in a venture backed software startup developing greenfield products strongly recommended

- Building and optimizing ‘big data’ data pipelines, architectures and data sets, using

    - Big data tools: Hadoop, Spark, Kafka, etc.

    - Cloud PaaS big data services: AWS, GCP, or Azure

- Applying analytic skills related to working with unstructured datasets

- Communicating, verbally and written, with both business and technical stakeholders to achieve product engineering objectives;

- Leading across all aspects of a technology solution such as integration, data, services, front-end, back-end, network, deployment, scaling, security, performance and development;

- Managing rapid-prototyping efforts with new and emerging technologies leveraging agile development techniques;

- Designing successful technical/integration architectures for large-scale platforms with a mix of 3rd party vendor, open-source, custom software, including the documentation of technical assumptions and decisions;