Data Engineer || Remote in USA ||

Hi   Hi, Greeting!! Role: Data Engineer Location: Remote in USA Duration : 6 months contract with potential extension Job description: Candidate should be comfortable working in PST. • Minimum 6 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 • Engage in the delivery and presentation of solutions Participate in data storage architecture design discussions • Apply machine learning and/or statistical techniques to time series classification and telemetry anomaly detection problems Thanks & Regards

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