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Manager Data Analytics Engineer Jobs in Iowa (NOW HIRING)

Data Engineer III

Des Moines, IA · On-site

$111K - $134K/yr

Balances and designs data analytics product solutions based on cost and performance to meet data ... Implements complex logical models into appropriate database management systems, considering ...

Bachelor's degree in Information Systems, Systems Engineering, Data Management, Data Analytics, Computer Science, Mathematics, Software Engineering, Statistics, Accounting, Finance, or a related ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Data Strategy-Manager

Des Moines, IA · On-site

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Data Engineer

Urbandale, IA · On-site

$80K - $120K/yr

Data Engineer As a Data Engineer, you will enable engineers, analysts, and data scientists to more ... Manage and optimize storage of diverse data types, including images, raster data, parquet files ...

... programming languages commonly used in data analysis, with exposure to data modeling. Exposure to data modeling, statistical methods, and machine learning techniques. * Experience managing semantic ...

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Manager Data Analytics Engineer information

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a Manager Data Analytics Engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
What are the most commonly searched types of Data Analytics Engineer jobs in Iowa? The most popular types of Data Analytics Engineer jobs in Iowa are:
What are popular job titles related to Manager Data Analytics Engineer jobs in Iowa? For Manager Data Analytics Engineer jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in Iowa look for? The top searched job categories for Manager Data Analytics Engineer jobs in Iowa are:
What cities in Iowa are hiring for Manager Data Analytics Engineer jobs? Cities in Iowa with the most Manager Data Analytics Engineer job openings:
Data Engineer III

Data Engineer III

EMC Insurance Companies

Des Moines, IA • On-site

$111K - $134K/yr

Full-time

Posted 13 days ago


EMC Insurance rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

9th of 281 rated insurance


Job description

At EMC, we’re all about working together to make an impact. As part of our team, you’ll have the opportunity to grow, contribute, and gain experience that matters. We strive to be caring leaders, close partners, and responsive experts—always supporting each other to do our best work. Join us, and let’s improve lives together.

Essential Functions:       

Develops, tests, and maintains complex prioritized engineering (design/build/test) work as a member of a data analytics product pipeline architecture and infrastructure team:

  • Investigates and analyzes feasibility of data integration prototypes and program requirements
  • Develops specifications and plans the full range of programming actions to produce data integration components
  • Develops and maintains complex automated ETL/ELT pipeline architecture that cleans, transforms, and aggregates data from disparate sources using architecturally approved tools, programming languages, and services to deliver a data mesh approach
  • Develops and maintains complex automated ETL/ELT monitoring and alarming solutions using architecturally approved languages and services
  • Monitors, troubleshoots, and optimizes data pipelines for quality, performance, and reliability creating a single source of truth providing business customers with highly reliable and quality data
  • Builds complex unit tests to enable test driven development and automation to drive code reliability
  • Develops, maintains, tests, and deploys code with architecturally approved toolsets using Dev Ops practices, ETL/ELT pipelines, data catalogs and data queries
  • Maintains data solutions in a divest state to ensure business functionality until replaced with new technology
  • Balances and designs data analytics product solutions based on cost and performance to meet data needs and business requirements
  • Guides business customers to develop, troubleshoot, and optimize complex SQL and ETL/ELT solutions to solve reporting, metrics, and analytics problems

Data analysis: Collaborates with cross-functional teams to understand data requirements for data analytics products and translate them into scalable and efficient data solutions:

  • Leads moderately complex projects or supports larger initiatives as part of a team
  • Partners with users and stakeholders to understand data needs and business requirements
  • Leads the team on conceptualizing and developing new data solutions to meet the business data needs and requirements
  • Researches, performs analysis, and proposes effective solutions related to system developments and enhancements through collaboration with Data Architecture
  • Analyzes and reviews potential adjustments or modifications for impacts on other programs
  • Leverages data governance, data security, and privacy principles to support data lineage and reference data needs
  • Collaborates with cross-functional teams to understand business and downstream application (BI reporting, Data Science, Data Governance, other System integrations) and consumer requirements to deliver data-driven solutions that implement best practices for data management, security, and governance

Data modeling:

  • Develops complex data objects for business analytics using data modeling techniques
  • Models front-end and back-end data sources to help draw a more comprehensive picture of user flows throughout the system and to enable powerful data analysis
  • Works with stakeholders to understand complex business needs and translates them into a conceptual data model, defining entities, attributes, and relationships 
  • Builds complex detailed logical models based on the conceptual model, specifying data types, constraints, and keys to ensure data integrity
  • Implements complex logical models into appropriate database management systems, considering database features, storage optimization, and performance considerations
  • Designs complex data pipelines to extract data from source systems, transform it as needed based on the data model, and load it into the target database

Documentation:

  • Participates in creating and maintaining documentation related to the design of applications and interfaces to enterprise and third-party systems in accordance with departmental and team standards
  • Collaborates with data governance on ensuring what is being produced in data analytics products enables data governance to publish a data asset
  • Collaborates with data governance to develop and maintain data analytic products, artifacts and user documentation for business customers
  • Works with business customers and software development teams to gather and document requirements for data publishing and data consumption via data mesh architecture
  • Maintains systems documentation

Education & Experience:

  • Bachelor’s degree, preferably in a computer related field or equivalent relevant experience
  • Five years of data integration development experience, or related experience

Knowledge, Skills & Abilities:

  • Strong SQL knowledge and experience working with relational databases
  • Excellent analytical skills to work with unstructured datasets
  • Excellent knowledge of applicable programming languages, such as Python
  • Strong knowledge of cloud services such as RDS, S3, SNS, CloudWatch and Lambda
  • Strong knowledge of DBT/Informatica or other ETL/ELT tools preferred
  • Strong knowledge of Snowflake
  • Strong knowledge of data modeling
  • Excellent ability to build processes supporting data transformation, data structures, metadata, dependency and workload management
  • Strong ability to manipulate, process and extract value from large, disconnected datasets
  • Strong knowledge of DevOps and/or DataOps practices, CI/CD pipelines, and containerization technologies preferred
  • Excellent knowledge of orchestration or scheduling tools
  • Excellent verbal and written communication skills
  • Strong attention to detail, organizational and multi-tasking skills with the ability to adapt to changing priorities
  • Ability to maintain confidentiality

The hiring salary range for this position will vary based on geographic location, falling within either of the following:

$92,670 - $128,045 or $102,443 - $140,845

A hiring range represents a subset of the full salary range. The actual salary will depend on several factors, including relevant education, skills, and experience of an applicant, geographic location, and business needs.

For information relating to the benefits EMC Team Members receive as part of a comprehensive rewards package, please visit www.emcins.com/careers.

Our employment practices are in accordance with the laws that prohibit discrimination due to race, color, creed, sex, sexual orientation, gender identity, genetic information, religion, age, national origin or ancestry, physical or mental disability, medical condition, veteran status, active military status, citizenship status, marital status or any other consideration made unlawful by federal, state, or local laws.

All of our locations are tobacco free including in company vehicles.


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