About SirionLabs:
Sirion is a Contract Lifecycle Management Leader! At least that’s what premiere analysts such as Gartner, Forrester, and IDC believe. We are SaaS innovators, working at the intersection of artificial intelligence and legal technology to transform how businesses contract for success. Our product is trusted by Fortune 500s and major global enterprises such as Schneider, Morgan Stanley, Qantas, Unilever, IBM, Vodafone, Alstom, and Novartis, to create, negotiate, and manage 5+ million contracts worth more than $450bn across 70+ countries around the world. We are on a hypergrowth journey and our recently closed $110 million Series D funding is adding to our momentum.
Job Role: Data Engineer
Years of Experience required: 5+ years.
Work Location: Gurgaon
Responsibilities for Data Engineer:
- Create and maintain optimal data pipeline architecture,
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- 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.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Direct the team as and when required.
**Qualifications for Data Engineer
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Partner with Data Scientist and Analytics professionals, designers, project managers, QA engineers, operations engineers, third-party systems providers, and other stakeholders in the Data ecosystem of the organization to ensure timely and correct access to data when needed.
- To be able to build scalable data access mechanism to achieve industrialization that would make data access easier for the Data Science and Analytics teams.
- Able to work on automation options for data access and data preparation.
- Ensure data quality and create checkpoints to assist in this process.
- Deployment support in regard to the creation of needed data pipelines and mechanisms within the data layer to support the implementation of AI & Machine learning based analytics solution/algorithms developed by data scientists.
- Design and develop program connectors needed to digest/offer data via APIs.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
**
Requirements
We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
They should also have experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.