Sr Data Engineer

Alignment Healthcare USA, LLC
Orange, CA, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$130,332.0 - $195,498.0
Working hours
Regular working hours
Job source

Tech stack

Sql Data Warehouse Java (Programming Language) .NET Framework Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Microsoft Azure Big Data Cloud Engineering Information Engineering Data Infrastructure Extract Transform Load (ETL)
+25 more
Data Mining Data Warehousing Linux Distributed Systems Elasticsearch Apache Hadoop Apache HBase Apache Hive Python (Programming Language) Machine Learning Metadata Microsoft SQL Server NoSQL Oracle (Applications) SQL Databases SQL Server Integration Services Systems Integration Teradata SQL Cloud Platform System Apache Spark Data Lakes Information Technology Api Design Data Pipelines Amazon Redshift

Job description

As a Data Engineer, you will develop a new data engineering platform that leverage a new cloud architecture, and will extend or migrate our existing data pipelines to this architecture as needed. You will also be assisting with integrating the SQL data warehouse platform as our primary processing platform to create the curated enterprise data model for the company to leverage. You will be part of a team building the next generation data platform and to drive the adoption of new technologies and new practices in existing implementations. You will be responsible for designing and implementing the complex ETL pipelines in cloud data platform and other solutions to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. “

General Duties/Responsibilities (May include but are not limited to):

  • Interfacing with business customers, gathering requirements and developing new datasets in data platform
  • Building and migrating the complex ETL pipelines from on premise system to cloud and Hadoop/Spark to make the system grow elastically
  • Identifying the data quality issues to address them immediately to provide great user experience
  • Extracting and combining data from various heterogeneous data sources
  • Designing, implementing and supporting a platform that can provide ad-hoc access to large datasets
  • Modelling data and metadata to support machine learning and AI

Requirements

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.The requirements listed below are representative of the knowledge, skill, and/or ability required.Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Minimum Experience:

3+ years relevant experience in cloud based data engineering.

Demonstrated ability in data modeling, ETL development, and data warehousing.

Data Warehousing Experience with SQL Server, Oracle, Redshift, Teradata, etc.

Experience with Big Data Technologies (NoSQL databases, Hadoop, Hive, Hbase, Pig, Spark, Elasticsearch etc.)

Experience in using Python, .net, Java and/or other data engineering languages

Education/Licensure:

Bachelors or Masters in Computer Science, Engineering, Mathematics, Statistics, or related field

Other:

Knowledge and experience of SQL Sever and SSIS.

Excellent communication, analytical and collaborative problem-solving skills

Preferred :

Healthcare domain and data experience

Healthcare EDI experience is a plus

API development experience is a plus

Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.

Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

Experience building data products incrementally and integrating and managing datasets from multiple sources

Experience leading large-scale data warehousing and analytics projects, including using Azure or AWS technologies - SQL Server, Redshift, S3, EC2, Data-pipeline, Data Lake, Data Factory and other big data technologies

Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space

Linux/UNIX including to process large data sets.

Experience with Azure, AWS or GCP is a plus

Microsoft Azure Certification is a plus

Demonstrable track record dealing well with ambiguity, prioritizing needs, and delivering results in an agile, dynamic startup environment

Problem solving skills and Ability to meet deadlines are a must

Microsoft Azure Certification is a plus

About the company

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together.

“Alignment Healthcare is a data and technology driven healthcare company focused partnering with health systems, health plans and provider groups to provide care delivery that is preventive, convenient, coordinated, and that results in improved clinical outcomes for seniors.

We are experiencing rapid growth (backed by top private equity firms), our Data Services and BI team is looking for the best and brightest leaders. Data drives the way we make decisions. We love our customers and understanding them better makes it possible to provide the best clinical outcome and care experience.

This position will play a key role in building and operating a cloud-based data platform and its pipelines using big data technologies.

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