Company Description:
Infostretch is a pure-play digital engineering services firm focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. We deliver custom solutions that meet customers’ technology needs wherever they are in their digital lifecycle. Backed by Goldman Sachs and Everstone Capital, Infostretch works with both large enterprises and emerging innovators -- putting digital to work to enable new products and business models, engage with customers in new ways, and create sustainable competitive differentiation.

Job Summary

As  a Data Engineer at  the Analytics  Centre  of  Excellence, you  shall be  very  hands-on,  level, you shall be responsible for building and maintaining a scalable and robust Data Platform involving development of complex data processing pipelines, ETL, data integration, . You shall work closely with our architect team to design and develop the Enterprise  Data  Platform. You  shall advocate  and inculcate best engineering practices in  the development of the Enterprise Data Platform. The Data Engineer is responsible for the development of analytics big data transformation flows on a large-scale service analytics platform for various in house customers. Responsibility includes delivery of high quality use case Data Pipeline ready for use and deployment towards customers, meeting the business requirements and aligning with the solution vision and strategy. The Data Engineer will have a strong influence on the technical design, and be expected to have a deep understanding of business and solution development context.

Key Responsibilities

• Create and maintain optimal data pipeline architecture for both stream processing and batch processing,
• 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 Business,  Product,  Data  and  Design  teams  to  assist  with  data-related technical issues and support their data infrastructure needs.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Required Knowledge/Skills/Abilities:

Must Haves

1. Data Engineer with at least 5to 10 years of experience in Batch and Stream Processing
2. Experience in Apache Spark and Apache Flink (Highly Desirable)
3. Experience in working with Apache Kafka, Kafka Connect
4. Very Strong in Analytical SQL
5. Experience developing large scale and high-volume data pipelines is a must
6. Experience in Java/Scala and/or Python

Highly Desirable

1. Experience on Ingestion, Rollups and Real Time Analytics with Apache Druid
2. Experience in Stateful Stream Processing in Apache Flink
3. Experience on AWS Data Analytics Stack -AWS EMR, AWS Lake Formation, AWS S3, AWS Glue,
4. Experience in Apache Airflow
5. Experience in Data Quality

Disclaimer:
If you feel that this is a good match for your skillsets, please submit a current word version of your resume along with a cover letter describing your skills, experience and salary expectations. We are an Equal Opportunity Employer (EOE). You can read our job applicant privacy policy here.