Data Engineer

TRIARQ Health India

TRIARQ Health is a Physician Practice Services company that partners with doctors to run modern patient-centred practices so they can be rewarded for delivering high-value care. TRIARQ’s Physician-led partnerships simplify practices’ transition to value-based care by combining our proprietary, cloud-based practice, care management platform and patient engagement services to help doctors focus on better outcomes.

Industry Type: IT-Software, Software Services
Division: Healthcare Technology
Location: Nashik, Pune

We are looking for a data engineer who will help us discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. Your primary focus will be to collect, organise, apply data mining techniques, doing statistical analysis, find patterns and building high quality prediction systems integrated with our products.

We will rely on you to build data products to extract valuable business insights. Your goal will be to help our company analyse trends to make better decisions. In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research in the process.


Job Responsibilities:

  • Build a scalable infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Google/AWS/Azure services this includes fixing coding errors and other data-related problems.
  • Enhancing the data mining process primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine for building analytic systems
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Performing initial analysis to assess the quality of the data by Processing, cleansing, and verifying the integrity of data pre-processing of structured and unstructured data which is used for analysis
  • Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Building models to address business problems
  • Build predictive models and machine-learning algorithms
  • Identify valuable data sources and automate data collection processes
  • Present information using data visualization techniques
  • Propose solutions and strategies to business challenges
  • Collaborating with engineering and product development teams, organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance.

Skills Required:

  • Proven experience as a Data Scientist or Data Analyst
  • Experience with big data tools: Cloud SQL, Pub/Sub, Apache Beam, Dataflow architectures, and datasets.
  • Experience in data mining Manipulating, processing, and extracting value from large, connected datasets.
  • Experience with batch/stream processing & highly scalable data warehouse.
  • Strong analytical skills related to working with structured/unstructured datasets.
  • Excellent understanding of machine learning techniques and algorithms
  • Experience using business intelligence tools such as Tableau, powerbi etc.
  • The ability to analyse, model and interpret data
  • Mathematical and statistical skills are also valuable to help gather, measure, organize, and analyse data.

Must Have Skills: SQL, Dataflow, Apache beam, Java/Python
Good to have Skills: MS SQL server, SSIS, MS Excel

Education: Graduate (Any stream), Post-Graduate (Preferred)
Work experience: 3+ years
Employment Type: Full Time Permanent (Candidate should be ready to give min. 2 yrs. of commitment)