Anaplan
FinOpsDataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“FinOps Data Engineer at Anaplan. Skills: Google Data Products, AWS Data Products, SQL, Python, ETL processes, data pipelines, data modeling. building and maintaining robust data pipelines. managing and transforming data”
What You'll Achieve.
optimize business decision-making; outpace their competition and the market; deliver high-quality data products and solutions
Industry & Context.
optimizing business decision-making; performance tuning
What They're Looking For.
Must Have
Bachelor’s degree in Computer Science, Information Technology, or a related field, 4-5 years of relevant experience in data engineering, particularly with cloud platforms like Google Cloud, 3 to 4 years of hands-on experience with Python, especially in handling semi/unstructured data and REST API integration, 3 to 4 years of experience working with relational databases like Google Big Query, AWS Athena, AWS Redshift, or at least MySQL/RDBMS, with a focus on writing optimized queries, 4 to 5 years of working knowledge with ETL tools (e. g. , Apache Airflow, Google Composer, AWS Glue or Informatica, MuleSoft, SSIS) and data modeling, 2 years of experience with Google BigQuery, Dataflow, and Cloud Composer, 2 years of experience with AWS S3, Glue, Athena, Redshift, API Gateway, Experience managing the complete data engineering lifecycle, including solution design, development, and operations, Familiarity with Agile project approaches (Scrum/ Kanban) and tools such as Jira
Nice to Have
Certifications in Google Cloud Platform or related data engineering tools
What You'll Do.
building and maintaining robust data pipelines
managing and transforming data
ensuring the quality and integrity of data across various platforms
Use Google Data Products including BigQuery
and Cloud Composer/ Apache Airflow to design
optimize and maintain data pipelines and workflows
Use AWS Data Products such as S3
API Gateway to design
optimize and maintain data pipelines and workflows
Implement and manage metadata
and data lineage using tools from AWS
GCP and Azure to ensure data integrity
relevance and compliance
Provide input into the end-to-end data engineering lifecycle
as well as project/ programme lifecycle including managing non-functional requirements
and performance tuning
and manage data storage solutions using SQL and NoSQL databases/virtual databses
ensuring data is efficiently structured and accessible
Work with semi-structured and unstructured data
including making ReST API calls
subscribing to message topics
using Python for data manipulation and transformation
Develop and maintain ETL processes using tools from AWS
and create data models to support business requirements
How You'll Work.
Team & Collaboration
Collaborate with stakeholders to design E2E solutions, including prototyping, usability testing, and data visualization, to meet business needs; Work closely with FinOps team, Engineering, Corporate BI Teams, and as needed with data scientists/ analysts, and other stakeholders to deliver high-quality data products and solutions
Process & Methodology
project/ programme lifecycle, managing non-functional requirements, Agile project approaches (Scrum/ Kanban)
Full Job Description
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Your Impact The Data Engineer will be responsible for building and maintaining robust data pipelines, managing and transforming data, and ensuring the quality and integrity of data across various platforms. The candidate will have hands-on experience with Google Data Products and AWS Data Products, metadata management tools, orchestration tools and strong expertise in SQL, Python, and ETL processes. Key Responsibilities: Google Data Products: Use Google Data Products including BigQuery, Dataflow, and Cloud Composer/ Apache Airflow to design, develop, optimize and maintain data pipelines and workflows. AWS Data Services: Use AWS Data Products such as S3, Glue, Athena, Redshift, API Gateway to design, develop, optimize and maintain data pipelines and workflows. Metadata Management & Data Quality: Implement and manage metadata, data quality, and data lineage using tools from AWS, GCP and Azure to ensure data integrity, relevance and com
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