You will be playing with volume and variety of the richest sales readiness data-set on the planet. You’ll be part of the team which not only stream/batch processing but serve API layer using Apache Spark and it’s one of a kind in the industry.
Data is a key of our business, the individual at this role will help drive the effort of its kind in the sales readiness industry to leverage data to surface prescriptive and predictive insights that serve as leading indicators of sales outcomes and activities.
What you’ll do:-
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements
- 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
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
- Work with data and analytics experts to strive for greater functionality in our data systems
- Mentor the team members
What you are:-
- You have 5+ years of experience in a Data Pipeline, Ingestion and data processing(Batch/Streaming)
- You have experience in building and optimizing 'big data' data pipelines, architectures and data sets.
- You have knowledge of message queuing, stream processing, and highly scalable 'big data' data stores
- You have advanced working experience with SQL(Relational)/NoSQL Data-bases knowledge and experience working with relational/ databases,
- You are strong in analytics related to working with unstructured datasets.
- You have experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- You have built processes supporting data transformation, data structures, metadata, dependency and workload management.
- You have worked with cross-functional teams in a dynamic environment.
Qualification & Tools exposure:-
- Graduate degree in CS, Statistics, Informatics, Information Systems or another quantitative field
- 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.