Senior Data Engineer

As part of the Mail Analytics Data Engineering team, you will be working on large-scale batch

pipelines, data serving, data lakehouse, and analytics systems, enabling mission critical

decision making, downstream, AI-powered capabilities, and more.

If you're passionate about building data infrastructure and platforms that power modern Dataand AI-driven business at scale, we want to hear from you!

Your Day

● Partner with Data Science, Product, and Engineering to collect requirements to define

the data ontology for Mail Data & Analytics

● Lead and mentor junior Data Engineers to support client Mail’s ever-evolving data

needs

● Design, build, and maintain efficient and reliable batch data pipelines to populate core

data sets

● Develop scalable frameworks and tooling to automate analytics workflows and

streamline users interactions with data products

● Establish and promote standard methodologies for data operations and lifecycle

management

● Develop new or improve and maintain existing large-scale data infrastructures and

systems for data processing or serving, optimizing complex code through advanced

algorithmic concepts and in-depth understanding of underlying data system stacks

● Create and contribute to frameworks that improve the efficacy of the management and

deployment of data platforms and systems, while working with data infrastructure to

triage and resolve issues

● Prototype new metrics or data systems

● Define and manage Service Level Agreements for all data sets in allocated areas of

ownership

● Develop complex queries, very large volume data pipelines, and analytics applications to

solve analytics and data engineering problems

● Collaborate with engineers, data scientists, and product managers to understand

business problems, technical requirements to deliver data solutions

● Engineering consulting on large and complex data lakehouse data

You Must Have

● BS in Computer Science/Engineering, relevant technical field, or equivalent practical

experience, with specialization in Data Engineering

● 8+ years of experience building scalable ETL pipelines on industry standard ETL

orchestration tools (Airflow, Composer, Oozie) with deep expertise in SQL, PySpark, or

scala.

● 3+ years leading data engineering development directly with business or data science

partners

● Built, scaled, and maintained Multi-Terabyte data sets and having an expansive toolbox

for debugging and unblocking large scale analytics challenges (skew mitigation,

sampling strategies, accumulation patterns, data sketches, etc.)

● Experience with at least one major cloud's suite of offerings (AWS, GCP, Azure).

● Developed or enhanced ETL orchestrations tools or frameworks

● Worked within standard GitOps workflow (branch and merge, PRs, CI / CD systems)

● Experience working with GDPR

● Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication

skills, ability to multitask and manage expectations

Preferred

● MS/PhD in Computer Science/Engineering or relevant technical field, with specialization

in Data Engineering

● 3+ years experience in Google Cloud Platform technologies (BiqQuery, Dataproc,

Dataflow, Composer, Looker)