Job type: Full-time

 

Responsibilities: (The primary tasks, functions, and deliverables of the role)

Design and build reusable components, frameworks, and libraries at scale to support 
analytics products.
Design and implement product features in collaboration with business and Technology 
stakeholders.
Identify and solve issues concerning data management to improve data quality.
Clean, prepare and optimize data for ingestion and consumption.
Collaborate on the implementation of new data management projects and re-structure of the 
current data architecture.
Implement automated workflows and routines using workflow scheduling tools.
Build continuous integration, test-driven development, and production deployment 
frameworks.
Analyze and profile data for designing scalable solutions.
Troubleshoot data issues and perform root cause analysis to proactively resolve product 
and operational issues.
 

Requirements:

Strong understanding of data structures and algorithms
Strong understanding of solution and technical design
Has a strong problem solving and analytical mindset?
Able to influence and communicate effectively, both verbally and written, with team 
members and business stakeholders
Able to quickly pick up new programming languages, technologies, and frameworks.
Experience building cloud scalable, real time and high-performance data lake solutions.
Fair understanding of developing complex data solutions
Experience working on end-to-end solution design.
Willing to learn new skills and technologies.
Has a passion for data solutions.
 

Required and Preferred Skill Sets:

Hands on experience in AWS - EMR [Hive, Pyspark], S3, Athena or any other equivalent cloud
Familiarity with Spark Structured Streaming
Minimum experience working experience with Hadoop stack dealing huge volumes of data in a 
scalable fashion.
hands-on experience with SQL, ETL, data transformation and analytics functions
hands-on Python experience including Batch scripting, data manipulation, distributable 
packages.
Experience working with batch orchestration tools such as Apache Airflow or equivalent, 
preferable Airflow.
Working with code versioning tools such as GitHub or BitBucket; expert level understanding 
of repo design and best practices
Familiarity with deployment automation tools such as Jenkins
Hands-on experience designing and building ETL pipelines; expert with data ingest, change 
data capture, data quality; hand on experience with API development.
Designing and developing relational database objects; knowledgeable on logical and 
physical data modelling concepts; some experience with Snowflake
Familiarity with Tableau or Cognos use cases
Familiarity with Agile; working experience preferred.