UsefulBI - Senior Data Engineer - Python/PySpark (4-15 yrs)

Position: Data Engineer

Location: Lucknow/Bangalore

About UsefulBI:

UsefulBI mission is to enable better business decisions through Business Intelligence. We do this by starting with a

deep understanding of the business context and business need. Our founding team collectively has 40+ years of experience in the domains we focus on and we staff each engagement with a functional expert who drives the business centricity through the engagement.

We are obsessed with being experts in the latest tools and technologies in our space - whether for data visualization, analysis or sourcing. Tableau, Qlik, Spotfire, Hadoop, R, SAS, etc. We are equally obsessive about our data science skills - we carefully select and apply the right data science algorithms and techniques to the right problems.

Overview :

UsefulBI is looking for highly skilled candidates, with expertise in generating power business insights from very large datasets, in this space where the primary aim would be to enable needle moving business impacts through cutting edge statistical analysis.

We are looking for passionate data engineers who can envision the design and development of analytical infrastructure which can support strategic and tactical decision-making.

The candidate should be well-versed in statistics, R and SAS languages, machine learning techniques, mathematics, and SQL databases. Python is also the most widely used programming language across the board when it comes to data engineering. Furthermore, a problem-solving, analytical knowledge of databases will also be a great asset. Should have AWS experience.

Experience Required :

- Minimum 5+ year's Experience in Data Engineering.

- Must have good knowledge and experience in Python.

- Must have good Knowledge of Pyspark.

- Must have good Knowledge of Databricks.

- Must have good experience in AWS (Glue, Athena, Redshift, EMR)

- Typically requires relevant analysis work and domain-area work experience.

- Expert in the management, manipulation, and analysis of very large datasets.

- Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

Key Responsibilities :

- 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.

- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.