Analytics Engineer

Abbott•Los Angeles, CA

1d•Onsite

About The Position

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries. Develop, constructs, tests, and maintains data architectures such as databases and large-scale processing systems, where the focus is on infrastructure and data flow management. They are responsible for building & maintaining data pipelines (ETL processes; ensuring data quality & reliability; designing and managing data warehouses and databases; and integrating data from various sources. Data engineers create the systems and structures that allow data to be collected, stored, & processed efficiently.

Requirements

Relevant skills include data mining, informatics, programming, information retrieval, databases and data structures, software engineering and systems design analysis.
Familiar with a range of mainstream commercial and open-source data tools, their constraints, advantages, disadvantages and areas of application; Has intermediate skill in using at least one such tool.
Familiar with data and statistical programming languages (such as SQL, SAS, R and Python).
Basic programming skills.
Ability to interpret an existing script of moderate complexity
Bachelors Degree (± 16 years) Computer Science, Information Technology, Data Analytics, Data Science or similar discipline including Databases, Mathematics, Statistics, Physics, or Engineering is preferred
Minimum 1 year Work experience with degree; or sufficient transferable experience to demonstrate functional equivalence to a degree
Training using mathematical modeling and statistical analysis
Basic experience of database applications
Basic knowledge of several tools (such as SAS, R or Python, SQL)

Nice To Haves

Prior experience/education in life sciences or healthcare preferred

Responsibilities

Assists in the deployment and monitoring of data pipelines and workflows under guidance from senior engineers.
Supports basic data quality initiatives & integration through testing and validation processes.
Builds basic analytic data sets for exploration and modeling.
Assists in the implementation of data security measures, compliance, standards, and policies.
Documents data processes, procedures, and workflows for knowledge sharing.
Assist with data pipeline development, data cleaning and preprocessing.
Works with Sr Engineers to understands how business needs are converted into analytical/technical requirements; provides input to data gathering.
Assists in the scoping, planning and delivery of projects.
Assists in data collection and cleansing efforts; focused on building and maintaining the infrastructure processes that automate data collection and cleansing.
Understands the fundamentals of big data storage and distribution systems and relevant software tools, their constraints, advantages and disadvantages.
Maintains awareness of trends and best practice approaches
Receives specific direction and guidance from more experienced team members.
Adapts to changing priorities as they arise.
Completes own work details and assignments of low complexity and guidance from senior level engineers.
Collaborates for results and participates in idea-sharing and solution development.
Escalates issues to more senior colleagues as required.
Works well with others in a collaborative, goal-driven environment.
Contributes to multiple projects to support analytical tasks, with a moderate to high level of support provided by colleagues.
Conducts data acquisition from relational databases and flat files.
Wrangles low-complexity data, selecting appropriate techniques, such as parsing, or an algorithm, to create a data structure relevant to the problem.
Seeks mentorship opportunities in the organization to gain a diverse perspective.