About Sandata Technologies: Sandata Technologies is the leading supplier of software technology solutions serving home care and I/DD agencies, managed care organizations, and state payer programs throughout the United States. The Sandata solution has been implemented by 15,000 Provider Agencies, 19 State Payers, and 50 MCO Payers to ensure their compliance with changes in regulatory/compliance requirements and ongoing complexities. We make it easier for these organizations to work together and to manage their businesses while also getting paid as quickly as possible.

Why work here: At Sandata, we are committed to creating a real and measurable Diversity, Equity, and Inclusion initiative. We will create a work culture where we are curious, celebrate, respect, and appreciate our unique diverse stories, and how we've come to where we are. We will do everything possible so that people know that we care about them as an individual and work to build equity in our people, systems, and processes. We are continuing to grow our efforts, and we will grow further together.

Our Data and Analytics team from Sandata is looking for a Data Reliability Engineer. Data is essential for all our decision-making needs whether it's related to product design, product effectiveness and efficiency. It gives us insights into how we can continue improving our service for our end users. We strive to help our clients discover patterns in in their business activity by utilizing curated data, which is also deeply valuable to us as it gives us insights into how we can continue improving our service for our users. Our focus is to provide our clients with the highest level of data availability and to deliver high quality data. Our Site Reliability Engineering team is seeking a highly hardworking Data Reliability Engineer with a strong technical background and passionate about diving deeper into Big Data to develop state of the art Data Solutions. The data reliability engineer is responsible for helping an organization deliver high data availability and quality throughout the entire data life cycle from ingestion to end products: dashboards, machine learning models, and production datasets You'll apply your expertise to solving business problems through innovation and engineering practices. Key skills are - Python, Java, AWS Services, Advanced knowledge of application, data, and infrastructure architecture disciplines, ETL, Airflow, Kafka, Spark Streaming, Data Architect, Application/System Architect, CI/CD. IaC, and Cloud Architecture and Security best practices.

The most important job for a data reliability engineer is to ensure high-quality data is readily available across the organization and trustworthy at all times. You'll be required to apply your depth of knowledge and expertise to all aspects of our Datawarehouse and Data Lake development, including machine learning lifecycle, as well as provide detailed documentation and present project objectives with stake holders or colleagues to focused on common goals. Our team is rapidly growing as we dive through our digital transformation. We embrace a culture of experimentation and constantly strive for improvement and learning. You will have access to vast technologies to achieve our objectives and sharpen your skills. You'll work in a collaborative, trusting, and active environment. We encourage creative solutions that are in the best interests of our customers. We give a lot of attention to professional experience, teamwork, whiteboarding and collaboration, in-person offsite meetings and virtual Lunch and learns, while having the flexibility to work fully remote. We provide support for professional training and certifications.

What you will do:

• Translate business needs to technical specifications
• Ensure high data availability throughout the organization with minimum data downtime
• Developing and implementing new technologies to ensure ongoing improvement of data reliability and data observability
• Defining business rules that determine data quality, assisting in writing tests that validate business rules, and performing rigorous testing to ensure data quality.
• Working closely with application, data platform, and data engineering teams to reconfigure data ingestion pipelines to be more reliable and continuously monitored.
• Manage data incidents and drive blameless post mortems with cross-functional teams.
• Be an extension of the BI and Analytics team. Support the design, build and deployment of BI solutions (e.g. reporting tools)
• Maintain and support data analytics platforms
• Assist in Creating tools to store data (e.g. OLAP cubes)
• Conduct unit testing and troubleshooting
• Evaluate and improve existing BI systems
• Collaborate with teams to integrate systems
• Develop and execute database queries and conduct analyses
• Develop and update technical documentation
• Collaborate with Engineering, PM, and Business stakeholders to evaluate the impact of the upcoming features on data warehouse and reporting
• Design and implement QA environment and processes allowing end to end testing of proposed changes from data ingestion to visualization
• Be an active participant and advocate of agile practice to ensure health and process improvements for your team
• Optimization of data warehouse by increasing data timeliness and solidifying the reusable data assets
• Define the processes and frameworks allowing the Analytics team to prepare enriched and aggregated data assets for reporting and data science
• Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid)
• Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts

What you will bring:

• Proven experience as a BI Developer or Data Scientist
• In-depth understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework
• Experienced with ELT processes to transform data, set up and schedule jobs with Domo workbench, Talend, DBT, Python, Airflow, and cron.
• Expertise in AWS (S3, Glue, Redshift, DMS, Apache Airflow, Kafka, Kenesis Firehose, EMR, RDS, EC2)
• Experience IaC, terraform to deploy infrastructure and pipelines.
• Familiarity with BI technologies (e.g. AWS DMS, Domo, etc.)
• Knowledge of SQL queries, SQL Server Reporting Services (SSRS) and SQL Server Integration Services (SSIS)
• Knowledge of Oracle integration with BI tools.
• Proven abilities to take initiative and be innovative
• Maintain detailed documentation of your work and changes to support data quality and data governance
• Ensure high operational efficiency and quality of your solutions to meet SLAs and support commitment to our customers (Data Science, Analytics teams)
• Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, Athena, AWS Glue Studio, PySpark) to query and process data
• Experience with at least one major MPP or cloud database technology (i.e. Redshift, Snowflake)
• Solid experience with data integration toolsets (i.e Hevo, Airflow) and writing and maintaining Data Pipelines
• Good Scripting skills, including Bash scripting and Python
• Familiar with Scrum and Agile methodologies
• You are a problem solver with strong attention to detail and excellent analytical and communication skills
• Bachelor's or master's degree in Information Systems, Computer Science or related field
• 7+ years' experience as a data warehouse engineer/architect designing and deploying data systems in a startup environment
• 6+ years of data engineering experience developing large data pipelines
• Strong SQL skills and ability to create queries to extract data and build performant datasets
• Mastery of database and data warehouse methodologies and techniques from transactional databases to dimensional data modeling, to wide denormalized datamarts
• Deep understanding of SQL-based Big Data systems and experience with modern ETL tools
• Expertise in designing data warehouses using Redshift (Snowflake will be considered)
• Fluency in different SQL techniques for data transformation and data analysis
• Experience developing data pipelines in Python
• Familiarity with software engineering best practices as they apply to the data engineering domain
• Understanding of creating visualizations and reports

Perks and Benefits:

• Medical, dental, and vision coverage
• Flexible Spending Account for health and dependent care
• Health Savings Account
• BenefitsVIP/Health Advocate
• Company paid Life insurance and STD
• 401(k) Plan
• Aflac STD, LTD, Critical Illness, Hospital, and Accident insurance
• Employee Assistance Program
• Tuition reimbursement & paid certification programs
• In-house product training programs
• Catalog of training courses for skills development
• Career Pathing for every department
• Employee Resource Groups (BIPOC, LGBTQ, Women, Military Veterans)
• Paid vacation, sick days, and holidays
• Paid lunch break
• Employee discounts and company perks
• Casual work environment
• Remote work
• Frequent employee events and fun social clubs
  

Sandata Technologies is an Equal Opportunity Employer M/F/Disabled/Vet