Senior Data Engineer (14684465)
Apply NowCompany: aKube, Inc.
Location: Burbank, CA 91505
Description:
Job Description
City: Burbank, CA
Onsite/ Hybrid/ Remote:Onsite, 3-4 days a week
Duration:18 months
Rate Range: $96/hr on W2 depending on experience (no C2C or 1099 or sub-contract)
Work Authorization: GC, USC, All valid EADs except H1b
Must haves:
1)5+ years Data Engineering experience
2) Airflow and Spark
2) Snowflake or Databricks
3) SQL
Additional Notes: Netflix background would be perfect or content related experience is ideal.
Required Education
Bachelor's Degree in Computer Science, Information Systems equivalent industry experience
Description
As a Senior Data Engineer, you will play a pivotal role in the transformation of data into actionable insights. Collaborate with our dynamic team of technologists to develop cutting-edge data solutions that drive innovation and fuel business growth. Your responsibilities will include managing complex data structures and delivering scalable and efficient data solutions. Your expertise in data engineering will be crucial in optimizing our data-driven decision-making processes. If you're passionate about leveraging data to make a tangible impact, we welcome you to join us in shaping the future of our organization.
Key Responsibilities:
Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines
Build tools and services to support data discovery, lineage, governance, and privacy
Collaborate with other software/data engineers and cross-functional teams
Tech stack includes Airflow, Spark, Databricks, Delta Lake, Snowflake, Kubernetes and AWS
Collaborate with product managers, architects, and other engineers to drive the success of the Core Data platform
Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, and more
Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams)
Be an active participant and advocate of agile/scrum ceremonies to collaborate and improve processes for our team
Engage with and understand our customers, forming relationships that allow us to understand and prioritize both innovative new offerings and incremental platform improvements
Maintain detailed documentation of your work and changes to support data quality and data governance requirements
Basic Qualifications
5+ years of data engineering experience developing large data pipelines
Proficiency in at least one major programming language (e.g. Python,Java, Scala)
Strong SQL skills and ability to create queries to analyze complex datasets
Hands-on production environment experience with distributed processing systems such as Spark
Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines
Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query).
Experience in developing APIs with GraphQL
Deep Understanding of AWS or other cloud providers as well as infrastructure as code
Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices
Strong algorithmic problem-solving expertise
Excellent written and verbal communication
Advance understanding of OLTP vs OLAP environments
Willingness and ability to learn and pick up new skill sets
Self-starting problem solver with an eye for detail and excellent analytical and communication skills
Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling
Familiar with Scrum and Agile methodologies
City: Burbank, CA
Onsite/ Hybrid/ Remote:Onsite, 3-4 days a week
Duration:18 months
Rate Range: $96/hr on W2 depending on experience (no C2C or 1099 or sub-contract)
Work Authorization: GC, USC, All valid EADs except H1b
Must haves:
1)5+ years Data Engineering experience
2) Airflow and Spark
2) Snowflake or Databricks
3) SQL
Additional Notes: Netflix background would be perfect or content related experience is ideal.
Required Education
Bachelor's Degree in Computer Science, Information Systems equivalent industry experience
Description
As a Senior Data Engineer, you will play a pivotal role in the transformation of data into actionable insights. Collaborate with our dynamic team of technologists to develop cutting-edge data solutions that drive innovation and fuel business growth. Your responsibilities will include managing complex data structures and delivering scalable and efficient data solutions. Your expertise in data engineering will be crucial in optimizing our data-driven decision-making processes. If you're passionate about leveraging data to make a tangible impact, we welcome you to join us in shaping the future of our organization.
Key Responsibilities:
Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines
Build tools and services to support data discovery, lineage, governance, and privacy
Collaborate with other software/data engineers and cross-functional teams
Tech stack includes Airflow, Spark, Databricks, Delta Lake, Snowflake, Kubernetes and AWS
Collaborate with product managers, architects, and other engineers to drive the success of the Core Data platform
Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, and more
Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams)
Be an active participant and advocate of agile/scrum ceremonies to collaborate and improve processes for our team
Engage with and understand our customers, forming relationships that allow us to understand and prioritize both innovative new offerings and incremental platform improvements
Maintain detailed documentation of your work and changes to support data quality and data governance requirements
Basic Qualifications
5+ years of data engineering experience developing large data pipelines
Proficiency in at least one major programming language (e.g. Python,Java, Scala)
Strong SQL skills and ability to create queries to analyze complex datasets
Hands-on production environment experience with distributed processing systems such as Spark
Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines
Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query).
Experience in developing APIs with GraphQL
Deep Understanding of AWS or other cloud providers as well as infrastructure as code
Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices
Strong algorithmic problem-solving expertise
Excellent written and verbal communication
Advance understanding of OLTP vs OLAP environments
Willingness and ability to learn and pick up new skill sets
Self-starting problem solver with an eye for detail and excellent analytical and communication skills
Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling
Familiar with Scrum and Agile methodologies