Python FullStack Engineer

Role & Responsibilities
·  Minimum 8 years of Data Engineering experience and 3 years in large scale Data Lake ecosystem
·  Proven expertise in Databricks, Spark Python/SQL, Scala
·  Have worked on multiple TBs/PBs of data volume from ingestion to consumption
·  Work with business stakeholders to identify and document high impact business problems and potential solutions 
·  First-hand experience with the complete software development life cycle including requirement analysis, design, development, deployment, and support 
·  Advanced understanding of Data Lake/Lakehouse architecture and experience/exposure to Databricks techniques 
·  Work on end-to-end data lifecycle from Data Ingestion, Data Transformation and Data Consumption layer. Versed with API and its usability
·  Have worked on telemetry, logs and real time data ingestion though API
·  Experience with analytics/visualization toolsets
·  Solid understanding of advanced data science/engineering Strong computer science fundamentals and good working knowledge of Scala, Python, Hive
·   Good design and architectural skills to build microservices 
·   Strong Python and/or SQL skills Ability to manipulate JSON/XML data and exposure with other data manipulation platforms 
·   Basic to advanced understanding of big data technologies such as Spark, Kafka, Airflow, APIs 
·   Basic to advanced understanding of ML Ops techniques such as supervised or unsupervised learning 
·   You are very motivated, highly passionate, and curious about new technologies. You take pride in your work and strive to achieve incredible results and possess excellent communication and planning skills.
·   Ability to work independently and handle your own development effort.
·   Excellent oral and written communication skills Learn and use internally available analytic technologies 
·   Build models at scale using vast amounts of structured and unstructured heterogeneous types of data 
·   Identify key performance indicators and establish strategies on how to deliver on these key points for analysis solutions Use educational background in data engineering and perform data mining analysis 
·  Work with BI analysts/engineers to create prototypes, implementing traditional classifiers and determiners, predictive and regressive analysis points