About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Data Engineer to own the layer everything else depends on: ingestion and transformation pipelines, storage and warehouse design, and the retrieval infrastructure that AI systems query. The role is fully remote across Latin America, aligned to your client's working day.

You will not be building pipelines that work until the schema changes. Azumo has shipped production data systems since 2016, and the work here is judged downstream: whether a model can be trained on what you deliver, whether a retrieval query returns the right passage, whether a number survives being questioned by the client.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Scientist lane owns the question and the method. The AI Engineer lane owns production behavior. The Software Engineer lane owns AI-augmented product delivery. This role is the Data Engineer lane, and it owns pipelines, storage, and the retrieval layer.

One question places the boundary: when the output is wrong, whose problem is it? "The data was missing, stale, or wrong by the time it arrived" is yours."The system did the wrong thing with data that was correct" is the AI Engineer's.

Not quite your profile? Check our other openings:

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services, operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company, product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together, the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them, which is exactly the job we're hiring for.

The Role

Location: New York, United States (Office) - Must be able to work office based in NYC

On-Site | Full-time

Compensation: $250K - $350K

We are hiring on behalf of our client, an industry-leading accelerator program focusing on the intersection of blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now collectively valued in the tens of billions, our client provides an exceptional launchpad for high-impact innovation.

In this role, the candidate will report directly to the Chief Technology Officer and take full end-to-end ownership of data products—from defining initial requirements to deploying reliable production systems. This is an entirely onsite role based in New York City (NYC) designed for an ambitious, self-directed builder who thrives in a fast-paced, high-agency environment without requiring extensive product management or dedicated platform engineering support.

Key Responsibilities

Location: Preference for NYC hybrid, but open to candidates in EST, including LATAM.

Hybrid/Remote | Full-time

Compensation: $140K - $180K

Our client is an innovative financial technology and digital asset infrastructure provider backed by world-class venture investors, including Paradigm and Dragonfly. Driven by a mission to transform how capital moves globally, the organization is pioneering next-generation financial architecture to ensure digital dollars serve as a trusted, accessible, and programmable public good. They develop full-service platforms and advanced stablecoin stacks designed to make issuing, managing, and integrating digital currencies seamless for developers, fintechs, and institutional partners worldwide.

Analytics Engineer

Full-time | On-site

Location: New York

We are a technology company leveraging AI and data to solve complex operational challenges in a life sciences context. We are seeking a highly motivated Analytics Engineer to build the robust data foundation that powers our operations, client reporting, and strategic growth. This is a high-autonomy, high-impact role essential for driving better, faster decisions across the entire organization.

As an Analytics Engineer, you will be the owner of our core data assets and practices. You will ensure data is clean, consistent, and readily available as a source of truth for all internal and external stakeholders, from product to leadership to key clients.

Key Responsibilities:

InfyStrat is seeking a skilled SAP Data Migration Specialist to join our dynamic team. In this role, you will be responsible for planning, executing, and managing data migration projects within SAP environments. You will work closely with various stakeholders to ensure that data is accurately transferred and integrated into SAP systems, following best practices and compliance standards. The ideal candidate should have extensive experience with SAP data migration tools and methodologies and possess a deep understanding of data transformation processes. At InfyStrat, we value innovation and efficiency; your expertise will be critical in enhancing our SAP data management capabilities. If you are passionate about data and SAP solutions, we invite you to apply and contribute to our exciting projects.

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our partner companies is currently looking for an IS Data Engineer based in Oregon, Washington, Utah, Idaho, Arizona, Nevada, Texas, Montana, or Wisconsin.

As an IS Data Engineer, you will play a crucial role in powering data-driven decision-making across the organization. You'll be responsible for building and optimizing robust data pipelines that transform raw data into curated, high-quality datasets for analysts, data scientists, and other business stakeholders. Your work will help automate and streamline the flow of data, ensuring it is both accessible and secure while enabling advanced analytics and machine learning. This is a highly collaborative role that involves working with multiple teams to meet emerging data needs and support business goals through innovative data engineering solutions.

Accountabilities: