Responsibilities:
- Must be able to write quality code and build secure, highly available systems.
- Assemble large, complex datasets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing datadelivery, re-designing infrastructure for greater scalability, etc with the guidance.
- Create datatools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Monitoring performance and advising any necessary infrastructure changes.
- Defining dataretention policies.
- Implementing the ETL process and optimal data pipeline architecture
- Build analytics tools that utilize the datapipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Create design documents that describe the functionality, capacity, architecture, and process.
- Develop, test, and implement datasolutions based on finalized design documents.
- Work with dataand analytics experts to strive for greater functionality in our data
- Proactively identify potential production issues and recommend and implement solutions
Skillsets:
- Good understanding of optimal extraction, transformation, and loading of datafrom a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Proficient understanding of distributed computing principles
- Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.
- Implemented complex projects dealing with the considerable datasize (PB).
- Optimization techniques (performance, scalability, monitoring, etc.)
- Experience with integration of datafrom multiple data sources
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,
- Knowledge of various ETL techniques and frameworks, such as Flume
- Experience with various messaging systems, such as Kafka or RabbitMQ
- Good understanding of Lambda Architecture, along with its advantages and drawbacks
- Creation of DAGs for dataengineering
- Expert at Python /Scala programming, especially for dataengineering/ ETL purposes

About Ganit Business Solutions
About
Ganit Inc. is in the business of enhancing the Decision Making Power (DMP) of businesses by offering solutions that lie at the crossroads of discovery-based artificial intelligence, hypothesis-based analytics, and the Internet of Things (IoT).
The company's offerings consist of a functioning product suite and a bespoke service offering as its solutions. The goal is to integrate these solutions into the core of their client's decision-making processes as seamlessly as possible. Customers in the FMCG/CPG, Retail, Logistics, Hospitality, Media, Insurance, and Banking sectors are served by Ganit's offices in both India and the United States. The company views data as a strategic resource that may assist other businesses in achieving growth in both their top and bottom lines of business. We build and implement AI and ML solutions that are purpose-built for certain sectors to increase decision velocity and decrease decision risk.
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