Dxc Technology
SeniorDataEngineering
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“Senior Data Engineering at Dxc Technology. Skills: Data Engineering, Big Data, Data Architecture, Data Pipelines. Develop data & analytics solutions. Create high-performance algorithms”
What You'll Achieve.
Drive the evolution of Data & Services products/platforms with an impact-focused on data engineering; Unleash the value of big data; Support business and client needs in a quantitative manner; Facilitate informed recommendations/decisions; Enhance the insights we get from running tests; Expand the ways and properties on which we can test and experiment; Generate business insights & recommendations; Determine the highest priority problems to solve; Make a decision; Collect data and feedback from product managers, clients, and other stakeholders; Inform future development; Track usage; Consistently focus on key drivers of organization value; Prioritize operational activities accordingly
Industry & Context.
Solving complex problems with multi-layered data sets; Ability to Solve complex problems with multi-layered data sets; Good troubleshooting and debugging skills
What They're Looking For.
Must Have
Working proficiency in using Python/Scala, Spark (tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms, Good programming skills in Java, spring boot, Junit, Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts, Knowledge in software development test approaches & frameworks, Familiarity with RESTful APIs and micro-services architectures, Experience in working with CI/CD, Experience in working with Cloud APIs (e. g. , Azure, AWS), Experience in working with SQL database like Postgres, Oracle, Comfortable in developing shell scripts for automation, Good troubleshooting and debugging skills, Proficient in standard software development, such as version control, testing, and deployment, Demonstrated knowledge of coding and data engineering, Ability to quickly learn and implement new technologies, Ability to Solve complex problems with multi-layered data sets, Ability to innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations, Ability to multi-task and attention to detail, Flexibility to work as a member of a matrix based diverse and geographically distributed project teams, Good communication skills - both verbal and written – and relationship, collaboration skills, and organizational skills
Nice to Have
hands-on experience with Hadoop big data tools (Hive, Impala, Spark), Experience with data pipeline and workflow management tools: NIFI, Airflow, Experience participating in complex engineering projects in an Agile setting e.g. Scrum
What You'll Do.
Develop data & analytics solutions
Create high-performance algorithms
Develop cutting-edge analytical techniques
Create intuitive workflows
Develop data-driven innovative analytical solutions
Identify opportunities to support business needs
Build automated data pipelines
Design data architecture/schema
Perform jobs in big data cluster
Provide support for deployed data applications
and incorporate new data sources
Enhance insights from running tests
Expand ways and properties to test
Streamline development
and running of data pipelines
Mentor junior colleagues
Participate in development of data and analytic infrastructure
Continuously innovate and determine new approaches
Partner with roles across organization
Evaluate trade-offs between analytics solutions
Break large solutions into smaller milestones
Evangelize releases to users
Implement or validate Data Lineage
Implement or validate Quality checks
Implement or validate classification
cross-functional teams
Establish team culture and processes
Focus on key drivers of organization value
Prioritize operational activities
Escalate technical errors or bugs
Maintain awareness of technical and product trends
How You'll Work.
Team & Collaboration
Partner with roles across the organization including consultants, engineering, and sales; Work with small, cross-functional teams; Flexibility to work as a member of a matrix based diverse and geographically distributed project teams; relationship, collaboration skills
Communication Scope
Good communication skills - both verbal and written
Process & Methodology
Break large solutions into smaller, releasable milestones
Full Job Description
**Job Description:** s a Senior Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Java, Kafka, Spark, R, etc. **Your Role** * Drive the evolution of Data & Services products/platforms with an impact-focused on data engineering. * Design and implement scalable data architecture and data pipelines. * Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. * Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers. * Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc. * Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and
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