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Data Stacks Jobs (NOW HIRING)

Airwallex

Data Science Director, Growth

San Francisco, CA · On-site

$300K - $320K/yr

Expert-level proficiency in SQL and Python/R, with experience overseeing modern data stacks (Airflow, Databricks, dbt, Snowflake). * Strategic Operator: Comfortable navigating business trade-offs ...

Aptiv PLC

Data Platform Architect

Walnut Creek, CA · On-site

$70.50 - $90.75/hr

Must have fluency in Wind River data stack: Fivetran, Snowflake, dbt, Tableau. Must be comfortable working with a wide range of stakeholders and functional teams, including executives. Must be ...

Aptiv

Data Platform Architect

Walnut Creek, CA

$70.50 - $90.75/hr

Must have fluency in Wind River data stack: Fivetran, Snowflake, dbt, Tableau. Must be comfortable working with a wide range of stakeholders and functional teams, including executives. Must be ...

Veryon

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Understanding of data lakehouse architectures and modern data stacks * Exposure to machine learning data pipelines or AI/ML readiness frameworks * Experience supporting revenue operations or finance ...

Dwyer Instruments, Inc.

Director, Data Engineering

Modern Data Stack Leadership: Oversee the transition from legacy BI tools to modern, self-service analytics platforms, ensuring the organization has the agility to derive insights from the data ...

Zemoso Tech Inc

Senior Software Engineers

Dallas, TX · On-site

$121K - $159K/yr

Company Description ZeMoSo Technologies provides product & data engineering solutions using open source Big Data stacks, Machine Learning and advanced custom visualizations. In the recent past, we ...

Zemoso Tech Inc

Senior Software Engineers

Dallas, TX · On-site

$121K - $159K/yr

Company Description ZeMoSo Technologies provides product & data engineering solutions using open source Big Data stacks, Machine Learning and advanced custom visualizations. In the recent past, we ...

CogniSoft Technologies

AI Systems Architect

Dallas, TX · Hybrid

$241K/yr

Expertise in designing agent data stacks & retrieval systems, including: * Vector databases * Hybrid search * Data freshness strategies * Memory systems * Graph reasoning * BM25 and advanced ...

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Data Stacks information

What are Data Stacks?

Data stacks refer to the combination of tools, technologies, and frameworks used to collect, store, process, and analyze data within an organization. A typical data stack might include data ingestion tools, databases, data warehouses, processing frameworks, and analytics platforms. The purpose of a data stack is to streamline the flow of data from its source to actionable insights, supporting business intelligence and decision-making. Common examples include the Modern Data Stack, which often uses tools like Fivetran, Snowflake, dbt, and Looker.

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

To thrive as a Data Engineer, you need strong skills in database design, data modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with tools such as SQL, Apache Spark, Hadoop, and cloud platforms like AWS or Google Cloud, as well as certifications in these technologies, is highly valued. Problem-solving abilities, attention to detail, and effective communication are important soft skills for this role. These skills are crucial for building reliable data pipelines, ensuring data quality, and supporting data-driven decision-making within organizations.

What is the difference between Data Stacks vs Data Analysts?

AspectData StacksData Analysts
Required CredentialsBachelor's in Computer Science, Data Science, or related fields; certifications like SQL, Python, or cloud platformsBachelor's in Statistics, Mathematics, or related fields; often certifications in Excel, SQL, or data visualization tools
Work EnvironmentTechnical teams, data engineering, software development environmentsBusiness units, reporting teams, data visualization platforms
Employer & Industry UsageTech companies, data-driven organizations, startupsFinance, marketing, healthcare, consulting firms

Data Stacks focus on building and managing the underlying data infrastructure, while Data Analysts interpret data to provide insights. Both roles require analytical skills, but Data Stacks professionals are more technical, working with data pipelines and databases, whereas Data Analysts focus on analyzing data to support decision-making.

What are some common challenges faced when managing modern data stacks, and how can they be addressed in this role?

Professionals managing modern data stacks often encounter challenges such as integrating diverse data sources, ensuring data quality, and maintaining system scalability as data volumes grow. Addressing these challenges typically involves collaborating closely with data engineers, analysts, and IT teams to implement robust data pipelines, automate data validation, and monitor system performance. Staying updated with evolving technologies and best practices is also crucial for proactive problem-solving and optimizing the data stack for business needs.
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What states have the most Data Stacks jobs? States with the most job openings for Data Stacks jobs include:
Data Stacks jobs near you

Product Owner - Alation Data Catalog

Purple Drive Technologies

Minneapolis, MN • On-site

Full-time

Posted 2 days ago

Job description

Overview:
Product Owner - Alation Data Catalog
Location: Minneapolis, MN (Onsite)
Experience: 8+ years
Relocation: OK
Job Summary
We are seeking a strategic and technically adept Product Owner to lead initiatives involving the Alation Data Catalog. This role will be responsible for defining and executing the product vision, roadmap, and delivery of data catalog capabilities that enhance data discovery, governance, and literacy across the organization.
Key Responsibilities
  • Define and maintain the product roadmap for Alation-based data catalog initiatives.
  • Align catalog capabilities with enterprise data strategy and business goals.
  • Collaborate with data stewards, analysts, engineers, and business users to gather requirements and feedback.
  • Act as the primary liaison between business and technical teams.
  • Create and manage a prioritized product backlog.
  • Write clear user stories and acceptance criteria for catalog features and enhancements.
  • Drive adoption of metadata standards, data lineage, and stewardship practices using Alation.
  • Ensure catalog content is accurate, up to date, and aligned with governance policies.
  • Promote data literacy and catalog usage through training, documentation, and internal advocacy.
  • Define KPIs to measure catalog adoption and data quality improvements.
  • Work closely with data engineers and architects to integrate Alation with data sources (e.g., Snowflake, AWS, data pipelines using AWS Glue, etc.).
  • Support automation of metadata ingestion and policy enforcement.

Required Qualifications
  • 8+ years of experience in data management, data governance, or product ownership.
  • Hands-on experience with Alation or similar tools (e.g., Collibra, OvalEdge, etc.).
  • Strong understanding of metadata management, data lineage, and data quality principles.

Preferred Qualifications
  • Experience with SQL and data modeling.
  • Knowledge of data privacy regulations (e.g., GDPR, CCPA).
  • Background in financial services, asset management, or regulated industries is a plus.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and modern data stacks.
  • Proficiency in Agile methodologies and tools (e.g., Jira, Confluence).
  • Excellent communication and stakeholder management skills.

Apply