Top 10 DataOps Jobs Aspirants Should Apply for in August

Top 10 DataOps Jobs Aspirants Should Apply for in August
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DataOps jobs are in high demand from DataOps engineers to be well placed in the data-centric market

Data science offers a wide range of data engineering jobs and DataOps jobs across the world in the data-centric market. DataOps vacancies are opening in all tech and data-related companies that need effective database management in 2022 and beyond. DataOps jobs include multiple roles including a DataOps engineer to build data products and engineer the production department with database management. The global DataOps platform market size is expected to hit US$57.90 billion in 2030 at a CAGR of 24.2%. Data engineering jobs also include the DataOps engineer profession with lucrative salary packages per annum. DataOps vacancies can be searched on professional platforms such as LinkedIn and many more while receiving more data engineering jobs. Let's explore some of the top ten DataOps jobs or DataOps vacancies to apply for in August 2022 to work for the effective database management system.

Top ten DataOps jobs in August 2022
DataOps engineer expert at Solvay

Location: Belgium/China/France/Portugal

Responsibilities: The engineer can take on the data-intensive portion of the data life cycle with a specific focus on automating jobs associated with cleaning, preparing, and wrangling the data within the data pipelines. It is essential to improve the availability, accessibility, and integration of data while implementing, maintaining, and supporting the platform data management environment(s) from ingestion to storage, encoding, preparation, and delivery to the respective users.

Qualifications: The candidate must have an Engineering degree with three years of experience as the specified role or five years of experience in DevOps implementation with a specialization in Ops than data and CI/CD.

Click here to apply

DataOps engineer at GeoPhy

Location: The Hague

Responsibilities: The engineer should help the development of infrastructure and framework for data quality assurance while contributing to decisions about the technology stack, particularly as it relates to end-to-end data flow and automation. It is essential to support the orchestration of data products by improving metadata solutions.

Qualifications: The candidate must have at least four years of experience in data engineering and software development with knowledge of SQL, Python, Scala, Spark, data modeling, Apache Airflow, and web applications.

Click here to apply

DataOps engineer at Adyen

Location: Amsterdam

Responsibilities: The engineer should create, maintain and iterate on the current data infrastructure, anticipate growth and look for structural changes required in the big-data offering at Adyen, as well as work closely with users of the data infrastructure and arrive at pragmatic solutions.

Qualifications: The candidate must have a solid background in designing, scaling, and maintaining data infrastructure solutions and sufficient knowledge of the Hadoop ecosystem (Hive, Yarn, HDFS) with Spark, and securing clusters with Ranger and Kerberos.

Click here to apply

DataOps engineer at Lenskart

Location: Bengaluru

Responsibilities: The engineer should ensure the performance, security, and availability of databases, and handle common database procedures, such as upgrade, backup, recovery, migration, etc. while profiling server resource usage, optimizing, and tweaking as necessary.

Qualifications: The candidate must have a strong knowledge of MySQL 5. x database management, Linux shell scripting, SQL and NoSQL databases, MongoDB, InnoDB, and many more.

Click here to apply

DataOps engineer at Jefferson Frank

Location: Oslo

Responsibilities: The engineer should help bring models into production and ensure they are running efficiently and securely, take care of the deployment of ML models in a live environment, as well as maintain an efficient and secure environment running in the Cloud.

Qualifications: The candidate must have an understanding of data science, data analytics, bash scripting, Terraform, Azure, networking, and security, as well as container technology.

Click here to apply

DataOps engineer at bubble

Location: Wokingham

Responsibilities: The role is for high visibility with end-to-end functionality with a greater level of verbal and written communication.

Qualifications: The candidate must have eight to ten years of experience in Azure DevOps, Data Bricks, ADF, Azure Integration, Docker, Kubernetes, OpenShift, ArgoCD, GitOps, Jenkins CI, and Ansible.

Click here to apply

DataOps engineer at E.ON Energie Deutschland GmbH

Location: Germany

Responsibilities: The engineer should continuously develop the modern data platform in the cloud with a focus on operation and the development and orchestration of ETL processes in cooperation with the data engineers. The duty also includes the provision and further development of monitoring, alerting and logging solutions for infrastructure, SaaS solutions and data pipelines.

Qualifications: The candidate must have a degree in computer science with sufficient experience in the Azure cloud components, CI/CD, Airflow, Python, SQL, Docker, Kubernetes, and other IT operations. It is necessary to know German at B2 level.

Click here to apply

DataOps engineer at FanDuel

Location: Remote in the UK

Responsibilities: The engineer should help in provisioning and maintaining infrastructure, building automated tools that will organize, model, and present data as a coherent product and offer it to stakeholders, as well as implementing data lake, warehouse, and lakehouse architectures leveraging the knowledge of data archiving and retrieval solutions.

Qualifications: The candidate must have a deep understanding of data lake permissions, AWS, GCP, data ingestion, SNS, SQS, Kafka, Spark, and IaC technology.

Click here to apply

DataOps engineer at Colgate-Palmolive

Location: Partial remote, New Jersey  

Responsibilities: The engineer should help establish DataOps platforms, processes, and frameworks to improve data quality and cycle times, and implement continuous integration and delivery of data pipelines while creating and implementing automated test frameworks for testing data pipelines.

Qualifications: The candidate must have a Bachelor's degree in any technical field with strong computer science fundamentals, cloud data technologies, Java, Python, and SQL.

Click here to apply

DataOps engineer- data analytics platform at ING

Location: Poland

Responsibilities: The role is to help in building cloud-ready state-of-the-art data analytics platform with data analytics platform components development and maintenance, SecOps activities, as well as Infra-as-Code.

Qualifications: The candidate must have sufficient experience in big data tools, Infra-as-Code, data ingestion pipelines, ML models, Alluxio, Trino, Superset, and Hive.

Click here to apply

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