Job Details

Data Engineer at SymphonyAI



Job Location



7,50,000 - 10,00,000


Within 1 Month

Work Experience

Fresher - 2 Years

Required Qualifications

PhD / Bachelor of Engineering / Bachelor of Technology / M. Tech / Master of Engineering /

Job Description

Data Engineer:

About the company

ConcertAI is the leading provider of precision oncology solutions for biopharma and healthcare, leveraging the largest collection of research-grade Real-world Data and the only broadly deployed oncology-specific AI solutions. Our mission is to improve translational sciences; accelerate therapeutic clinical development; and provide new capabilities for post-approval studies to accelerate needed new medical innovations to patients and to improve patient outcomes. ConcertAI has emerged as one of the highest growth technology companies in Real-world Data and AI, backed by industry leading private equity companies: SymphonyAI, Declaration Partners, Maverick Ventures, and Alliance|Bernstein.

ConcertAI is transforming how healthcare is delivered and dedicated to improving patient outcomes in oncology by offering innovative solutions on how data and intelligence is used to solve healthcare problems. We are creating something special in our culture, by building a collaborative, engaged, patient focused, team approach to our mission. Our high-performance teams are looking to add great talent to the mix and we are hiring for the right mix of new skills and diverse mindset.

Job Description:

We are looking for energetic, self-motivated and exceptional Data Engineer to work on extraordinary enterprise products based on AI and Big Data engineering. He/she will work with star team of Architects, Data Scientists/AI Specialists, Data Engineers, Integration Specialists and UX developers.

Role and Responsibilities:

  1. Create and maintain optimal data pipeline architecture.
  2. Assemble large, complex data sets that meet functional / non-functional business requirements.
  3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  4. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
  5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  6. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  7. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  8. Work with data and analytics experts to strive for greater functionality in our data systems.
  9. Support software developers, database architects, data analysts and data scientists on data initiatives and ensure optimal data delivery architecture throughout projects.

Skills and Qualifications:

  1. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  2. Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
  3. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  4. Strong analytic skills related to working with unstructured datasets.
  5. Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  6. Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
  7. Experience supporting and working with cross-functional teams in a dynamic environment.
  8. 6+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Information Systems or another quantitative field. Should have experience using the following software/tools:

A)Experience with big data tools (AWS S3, RDS, Lambda, GLUE)

B)Experience with relational SQL and NoSQL databases, including Postgres and RDS- MSSQL.

C) Experience with object-oriented/object function scripting languages: Python, Pyspark etc.

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