Senior Associate - Software Development at Sutherland

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

04 Jun, 26

Salary

0.0

Posted On

06 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

BigQuery, Cloud Dataflow, Cloud Storage, ETL, GCS, Airflow/Composer, SQL, Python, Dataflow, DataProc, Data Analysis, Database Design, Data Migrations, Performance Tuning, Datastore, Bigtable

Industry

IT Services and IT Consulting

Description

Company Description We make digital 𝐡𝐮𝐦𝐚𝐧™ by combining human-centered design with real-time Analytics, AI, Cognitive Technology & Automation to create exceptionally engineered Brand Experiences! Sutherland is an experience-led digital transformation company. Our mission is to deliver exceptionally engineered experiences for customers and employees today, that continue to delight tomorrow. For over 35 years, we have cared for our customers’ customers, delivering measurable results and accelerating growth. Our proprietary, AI-based products and platforms are built using robust IP and automation. We are a team of global professionals, operationally effective, culturally meshed, and committed to our clients and to one another. We call it One Sutherland. #MakeDigitalHuman. https://www.sutherlandglobal.com/ https://www.linkedin.com/posts/sutherland-global_sutherland-india-is-certified-as-a-great-activity-6914801835199385600-wvHQ?utm_source=linkedin_share&utm_medium=member_desktop_web Job Description Sutherland is seeking an attentive and technical person to join us as a GCP Data Engineer specializing in planning, building, and managing data pipelines on Google Cloud Platform (GCP). We are a group of dynamic and driven individuals. If you are looking to build a fulfilling career and are confident you have the skills and experience to help us succeed, we want to work with you! Responsibilities: Keep management updated: Should update the management on the status. Impact the bottom line: Produce solid and effective strategies based on accurate and meaningful data reports and analysis and/or keen observations Define Sutherland’s reputation: Oversee and manage performance and service quality to guarantee customer satisfaction Strengthen relationships: Establish and maintain communication with clients and/or team members; understand needs, resolve issues, and meet expectations Take the lead: Able to debug the production issue quickly and provide the root cause analysis with resolution for the issue. Qualifications To succeed in this position, you must: This technical position will be responsible for designing data solutions using Google’s managed services such as Big Query, Cloud Dataflow, and Cloud Storage. Hands on experience and clarity on Big query, ETL, GCS, Airflow/Composer, SQL, Python and Pipeline development experience using Dataflow or DataProc. Very Good Experience in Data Analysis, Data mapping, Database design, Data migrations and performance tuning. Design, develop, and maintain data pipelines on GCP. Monitor and maintain the health of the data infrastructure and troubleshoot and resolve data-related issues Any other GCP services or databases like Datastore, Bigtable, Spanner, Cloud Run, Cloud Functions etc. Certification on Professional Google Cloud Data engineer will be an added advantage. Support QA (resolve issues and release fixes) UAT and production support when required. Deployment and integration testing of developed components in Development and Test environments. Years of Experience: 3 to 5. Educational Qualification: B.E / B.Tech / M.C.A Additional responsibilities: Knowledge of Hadoop ecosystem and its components –Hive, Impala, Sqoop, Oozie, etc. Basic Linux commands Analytical and problem-solving skills. Should Have strong verbal and written communication skills. US Health Care Knowledge. Any other ETL tools.

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Responsibilities

The role involves designing, building, and managing data pipelines on Google Cloud Platform (GCP) using managed services like BigQuery and Cloud Dataflow. Responsibilities also include monitoring data infrastructure health, troubleshooting issues, and providing root cause analysis for production problems.