Azure Data
Engineer
- Must Have: Databricks, Azure Synapse, Azure Data factory Azure Data Lake, Pyspark
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What we do for you
Design data strategy
We design and build an effective data strategy to support your enterprise business strategy by carefully considering to everyone in your organization. Configure and extend data for all functional use-cases, including transactional analytics and reporting, data science, digital and operational.
Build a modern data architecture
A modern data architecture allows you to build a scalable data lake, and use a broad and deep collection of purpose-built data services that provide the performance required for use cases such as low latency streaming analytics, interactive dashboards, log analytics, big data processing, and data warehousing.
Data transformation & Pipelines
At BigLynx, when data is being moved or when various data types needs to be analysed - we secure data sharing that eliminates the need for data extraction or transformation between departments, geographies, or partners We build a Building a path from ingestion to analytics.
HIRING THE BEST TALENT
IN DATA ENGINEERING
In an ever-changing world that includes new global trends and increased adoption of AI & Machine Learning (ML), automation & cloud migration, employees and organizations are in constant demand of new and improved skills to manage data. Data Engineering has seen a significant shift towards “real-time data pipelines and real-time data processing systems.” with “data as it is" impacted by Internet of Things (IoT), serverless computing and hybrid cloud and AI.
BigLynx, a technology startup in Seattle is exclusive to Data engineering talent & solutions for emerging organizations. We are hiring, upskilling and coaching our employees to lead the future of data Engineering.
#dataacquisition . #dataprocessing . #datagovernance . #datawrangling . #datavisualization . #datamodelling . #datatraining . #dataserving . #dataai . #datacloud
Learn and grow
Data Engineering seems to be a promising career for the next 5 years, as hundreds of data sources are emerging day by day. Nowadays, all major companies are looking for data engineers. Apart from that many IT companies are providing data services to major tech giants, which leads to a high job opportunity for a data engineer in the upcoming future. In a short while, this has become one of the highest paying jobs and it will remain the same in the upcoming years.
1. Python:
Python is a top skill for software engineers, machine learning engineers, and data scientists. Thus, it is no surprise that over 61% of data engineering roles mentioned these skills. The Python language and its libraries are very suited to building pipelines and workflows for data engineering. It’s also the native language of major workflow management platforms such as Airflow and Kubeflow.
Data Engineers also need a love of or at least an interest in data, in finding patterns in data, otherwise they may find the work boring. Also, Data Engineers have to like and have the ability to create systems that are difficult and complex. Big data projects are 10 times more complex than small data. So it's a love of data combined with a love of programming to create data pipelines.
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OUR OPEN POSITIONS
Azure Data
AWS Big
Data Engineer
- Must Have: SQL-on-Hadoop technology, AWS DynamoD, Redshift, S3, EMR, Glue, Redshift, Athena
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Dynamics
365 Developer
- Snowflake or Redshift, Kafka, Storm, RabbitMQ, Pyspark, Hive, Spark, Kafka, MapR
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