Data Software Engineer Staff

Panasonic•Irvine, CA

About The Position

The Data Software Engineer Staff is responsible for data acquisition, transformation, analytics, and operationalization to drive high-visibility, cross-division outcomes. The role leads investigation, evaluation, and testing initiatives; supports software developers, database architects, and data scientists; and delivers data solutions. The position develops distributed, scalable, and reliable pipelines for real-time, large-scale data ingestion and processing; creates data environments and datasets for a range of users; conducts offline analysis of large datasets; and troubleshoots complex data provenance, metadata, and engineering issues. It also investigates and recommends technical solutions and authors ETL scripts to curate data for data lakes, warehouses, and marts. The engineer owns product features from development through production deployment, designs and implements Hadoop EMR clusters and big data infrastructure, and deploys Hadoop, Spark, and database storage infrastructure in AWS. The role evaluates big data technologies, monitors and installs relevant software, develops tools and procedures to automate and monitor systems, collaborates on data tools, and advises on technical aspects of product backlog requests. The listed salary range is $119,000–$200,000 annually. The posting also states that the final offer may vary based on factors including knowledge, skills, experience, and location, and gives a separate range of $112,000–$188,000 annually.

Requirements

Bachelor’s degree in computer science, computer engineering, or a related technical field, or 12+ years of related data software engineering experience in lieu of a bachelor’s degree.
8+ years of professional experience as a data software engineer; or 12+ years of related experience as a data software engineer in lieu of a bachelor’s degree.
At least 2 years of experience with AWS cloud computing design, provisioning, and tuning.
Previous experience as a data engineer, database administrator, and/or business intelligence analyst.
Proven knowledge of database concepts, object and data modeling techniques, and design principles.
Proven knowledge of database architectures, software, and facilities.
Advanced experience with Python (required); Scala, Ruby, and R are also listed.
Advanced experience with SQL, database performance tuning, AWS RDS, Redshift, and MySQL.
Advanced experience with big data batch processing tools, including Hadoop MapReduce, Elasticsearch, PIG, Hive, Cascading/Scalding, Apache Spark, and AWS EMR.
Advanced experience with stream-processing systems, including Kinesis, Kafka, and MQTT.
Advanced experience with relational and NoSQL databases, including DynamoDB.
Experience with code, build, and deployment tools, including Git, Jenkins, and AWS Code.
Excellent verbal and written communication skills to collaborate, present and explain technical information, and advise management.
Ability to lead complex issues requiring in-depth evaluation of variable factors and sound judgment in selecting methods, techniques, and evaluation criteria.
Proven experience handling complex technical and business matters.
Ability to champion significant projects, programs, and business initiatives with creativity and ingenuity.
Ability to lead and mentor junior engineers and colleagues.
Valid authorization to work in the United States.

Nice To Haves

Related AWS certification.

Responsibilities

Develop distributed, scalable, reliable data pipelines for real-time, large-scale data ingestion and processing.
Create data environments and datasets for data scientists, data analysts, business analysts, and other users.
Perform offline analysis of large datasets using big data ecosystem components.
Troubleshoot complex data provenance, metadata, and engineering issues, including root-cause analysis and coordination with technical staff across organizations.
Investigate, evaluate, test, and recommend technical solutions for future systems.
Author ETL scripts to move and curate data for data lakes, data warehouses, and data marts.
Own product features from development through production deployment.
Provide solutions for the design and implementation of Hadoop EMR clusters and big data infrastructure.
Deploy Hadoop, big data, Spark, and database storage infrastructure in AWS cloud.
Evaluate big data technologies and prototype solutions to improve data processing architecture.
Monitor and install HDFS, Hadoop, Spark, and related software releases and third-party utilities, emphasizing system performance.
Develop tools and procedures to monitor and automate system tasks on servers and clusters.
Collaborate with other teams to design, develop, and deploy data tools for operational and product use cases.
Evaluate and advise on technical aspects of open product backlog requests with the project lead.
Lead complex technical issues and significant projects, programs, and business initiatives; mentor junior engineers and colleagues.

Benefits

Exempt salaried employees receive unlimited paid time off; non-exempt hourly employees accrue 14 vacation days, 7 sick days, and 3 personal days annually, with accrual increasing with tenure.
11 company-paid holidays annually and a paid company-wide U.S. shutdown between Christmas and New Year.
Medical insurance options through Aetna and Kaiser (California and Hawaii), with employee-only, employee-plus-spouse/domestic-partner, employee-plus-children, and family coverage options.
Dental PPO and DMO options and vision insurance through EyeMed or VSP.
401(k) with a 50% match on up to an 8% contribution, fully vested from day one.
Wellness program and counseling services.
Flexible spending and health savings accounts.
Life insurance for employees, spouses, and children; AD&D insurance; short- and long-term disability insurance; critical illness insurance; and accident insurance.
Legal assistance, pet insurance, and identity theft protection.
Dependent care FLSA, education assistance, commuter program, employee purchase program, and service award program.