Koantek
https://koantek.comAbout
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PythonThe Sr AWS/Azure/GCP Databricks Data Engineer at Koantek will use comprehensive
modern data engineering techniques and methods with Advanced Analytics to support
business decisions for our clients. Your goal is to support the use of data-driven insights
to help our clients achieve business outcomes and objectives. You can collect, aggregate, and analyze structured/unstructured data from multiple internal and external sources and
patterns, insights, and trends to decision-makers. You will help design and build data
pipelines, data streams, reporting tools, information dashboards, data service APIs, data
generators, and other end-user information portals and insight tools. You will be a critical
part of the data supply chain, ensuring that stakeholders can access and manipulate data
for routine and ad hoc analysis to drive business outcomes using Advanced Analytics. You are expected to function as a productive member of a team, working and
communicating proactively with engineering peers, technical lead, project managers, product owners, and resource managers. Requirements:
Strong experience as an AWS/Azure/GCP Data Engineer and must have
AWS/Azure/GCP Databricks experience. Expert proficiency in Spark Scala, Python, and spark
Must have data migration experience from on-prem to cloud
Hands-on experience in Kinesis to process & analyze Stream Data, Event/IoT Hubs, and Cosmos
In depth understanding of Azure/AWS/GCP cloud and Data lake and Analytics
solutions on Azure. Expert level hands-on development Design and Develop applications on Databricks. Extensive hands-on experience implementing data migration and data processing
using AWS/Azure/GCP services
In depth understanding of Spark Architecture including Spark Streaming, Spark Core, Spark SQL, Data Frames, RDD caching, Spark MLib
Hands-on experience with the Technology stack available in the industry for data
management, data ingestion, capture, processing, and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc
Hands-on knowledge of data frameworks, data lakes and open-source projects such
asApache Spark, MLflow, and Delta Lake
Good working knowledge of code versioning tools [such as Git, Bitbucket or SVN]
Hands-on experience in using Spark SQL with various data sources like JSON, Parquet and Key Value Pair
Experience preparing data for Data Science and Machine Learning with exposure to- model selection, model lifecycle, hyperparameter tuning, model serving, deep
learning, etc
Demonstrated experience preparing data, automating and building data pipelines for
AI Use Cases (text, voice, image, IoT data etc. ). Good to have programming language experience with. NET or Spark/Scala
Experience in creating tables, partitioning, bucketing, loading and aggregating data
using Spark Scala, Spark SQL/PySpark
Knowledge of AWS/Azure/GCP DevOps processes like CI/CD as well as Agile tools
and processes including Git, Jenkins, Jira, and Confluence
Working experience with Visual Studio, PowerShell Scripting, and ARM templates. Able to build ingestion to ADLS and enable BI layer for Analytics
Strong understanding of Data Modeling and defining conceptual logical and physical
data models. Big Data/analytics/information analysis/database management in the cloud
IoT/event-driven/microservices in the cloud- Experience with private and public cloud
architectures, pros/cons, and migration considerations. Ability to remain up to date with industry standards and technological advancements
that will enhance data quality and reliability to advance strategic initiatives
Working knowledge of RESTful APIs, OAuth2 authorization framework and security
best practices for API Gateways
Guide customers in transforming big data projects, including development and
deployment of big data and AI applications
Guide customers on Data engineering best practices, provide proof of concept, architect solutions and collaborate when needed
2+ years of hands-on experience designing and implementing multi-tenant solutions
using AWS/Azure/GCP Databricks for data governance, data pipelines for near real-
time data warehouse, and machine learning solutions. Over all 5+ years' experience in a software development, data engineering, or data
analytics field using Python, PySpark, Scala, Spark, Java, or equivalent technologies. hands-on expertise in Apache SparkTM (Scala or Python)
3+ years of experience working in query tuning, performance tuning, troubleshooting, and debugging Spark and other big data solutions. Bachelor's or Master's degree in Big Data, Computer Science, Engineering, Mathematics, or similar area of study or equivalent work experience
Ability to manage competing priorities in a fast-paced environment
Ability to resolve issues
Basic experience with or knowledge of agile methodologies
AWS Certified: Solutions Architect Professional
Databricks Certified Associate Developer for Apache Spark
Microsoft Certified: Azure Data Engineer Associate
GCP Certified: Professional Google Cloud Certified
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