Staff Data Pipeline Engineer
Posted on: August 6, 2022
Pocket empowers people to discover, organize, consume, and share
content that matters to them. Our apps and platform are essential
ways that tens of millions of people discover and consume content
on the web. Pocket is the Web, curated: for you and by you.
For content recommendations, everything starts with data. Pocket's
Data Products team builds systems that combine machine learning
with editorial expertise to surface high-quality content from
across the internet. Ensuring data privacy when collecting,
distributing, validating, and securing data at scale is no small
task and every engineer on our team plays a vital role in shaping
each user's experience.
We are looking for a Lead Data Pipeline Engineer to own the design
and development of data pipeline applications for complex,
extensible, and highly scalable cloud-based data platforms. Are you
passionate about building intuitive data models? Do you excel at
taking vague requirements and crystallizing them into scalable data
solutions? We invite you to apply!
People who excel on our team thrive in a small, dynamic
environments. We cover many areas including machine learning,
product engineering, machine learning operations, and data
modeling, among others.
Who You Are
- Enjoy working on small, dynamic teams.
- Understand Data Lifecycle and concepts such as lineage,
governance, privacy, retention, anonymity, etc.
- Conceptually familiar with AWS cloud resources (S3, EC2, RDS
- A trusted authority in distributed data processing
- Highly proficient in at least one of Java, Python or
- Comfortable with complex SQL
- Experience designing, building, and maintaining data lakes.
What You'll Do
- Build and maintain data pipeline applications
- Design, create and maintain the data platform data model at the
conceptual, logical, and physical levels.
- Establish data security, quality, load, transport and
- Research, design, document and modify data pipeline software
specifications throughout the production life cycle.
- Develop and maintain stakeholder documentation and operations
procedures, programs, security, etc. and assist in eliminating
- redundancy and automating manual processes.
- Assist in developing standards and criteria for the successful
implementation of new systems.
- Perform code reviews and mentor other engineers.
- Cloud warehouses: Snowflake, BigQuery, Redshift
- Feature stores: Sagemaker, Databricks, Vertex
- Orchestrators: Airflow, Prefect
- Compute frameworks: AWS Glue, Spark, Hadoop, Athena
- Streaming data: Kinesis, Kafka
- Data modeling: DBT
Commitment to diversity, equity, inclusion, and belonging
Mozilla understands that valuing diverse creative practices and
forms of knowledge are crucial to and enrich the company's core
mission. We encourage applications from everyone, including members
of all equity-seeking communities, such as (but certainly not
limited to) women, racialized and Indigenous persons, persons with
disabilities, persons of all sexual orientations, gender identities
We will ensure that qualified individuals with disabilities are
provided reasonable accommodations to participate in the job
application or interview process, to perform essential job
functions, and to receive other benefits and privileges of
employment, as appropriate. Please contact us at
email@example.com to request accommodation.
We are an equal opportunity employer. We do not discriminate on the
basis of race (including hairstyle and texture), religion
(including religious grooming and dress practices), gender, gender
identity, gender expression, color, national origin, pregnancy,
ancestry, domestic partner status, disability, sexual orientation,
age, genetic predisposition, medical condition, marital status,
citizenship status, military or veteran status, or any other basis
covered by applicable laws. Mozilla will not tolerate
discrimination or harassment based on any of these characteristics
or any other unlawful behavior, conduct, or purpose.
Req ID: R1866
Keywords: Mozilla, Austin , Staff Data Pipeline Engineer, Engineering , Austin, Texas
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