Verified Job
IT / Software / Data Analyst
Senior Data Engineer- job post Lektik Software
IT / Software / Data Analyst
#804155
Remote / WFH
Lektik Software
Job Description
Full job description
As a Data Engineer, you own the data layer that everything else depends on. That means building and operating the pipelines that move data out of our operational systems and third-party platforms into Snowflake, modeling and aggregating it there, and pushing the results back out to where the business actually uses them: HubSpot for go-to-market, plus our BI and reporting tools. You're the person who makes a number trustworthy. When a leader asks how a cohort of dealerships is performing, or when the AI team needs clean labeled outcomes to train on, your work is what answers the question. This is a build role, not a maintenance role. The warehouse is early enough that you'll shape the models, the conventions, and the tooling.
WHAT YOU'LL DO
- Build and operate reliable pipelines that land data from our operational databases, product systems, and third-party platforms into Snowflake.
- Model and aggregate data in Snowflake into well-documented, trustworthy tables that analysts, leadership, and engineers can build on.
- Sync aggregated data back into HubSpot so go-to-market teams work from accurate, current information.
- Feed and support our BI and reporting tools, and help define the metrics behind them.
- Own data quality end to end: validation, freshness and volume monitoring, alerting, and backfills when something goes wrong.
- Manage schema evolution and pipeline changes without breaking downstream consumers.
- Partner with engineering to make sure v2.0 emits the events and data the warehouse needs, rather than reverse-engineering it after the fact.
- Support the AI side of the business by turning raw conversation and outcome data into clean, labeled datasets.
WHAT WE'RE LOOKING FOR
- Strong SQL. You can write, read, and debug complex analytical SQL, and you care about how it performs.
- Hands-on experience with Snowflake, or a comparable cloud warehouse and the ability to ramp fast.
- Experience building production data pipelines, including orchestration, incremental loads, and idempotent reprocessing.
- Strong Python for data work.
- Experience with dimensional or analytics data modeling, and with a transformation framework such as dbt.
- Experience integrating with SaaS platforms and their APIs. HubSpot experience is a plus, as is CRM or marketing data experience generally.
- Experience with BI tooling and building datasets other people report from.
- Hands-on experience with AWS.
- Excellent debugging skills. You enjoy chasing a problem to its actual root cause, including "why does this number look wrong."
- An AI-first development approach. You are comfortable and effective using Claude as a daily part of how you build, review, and debug, not an occasional novelty.
- Excellent communication skills. You can explain a metric definition to a non-technical stakeholder and get agreement on it.
- Excellent communication skills, including writing clearly about technical decisions.
- A hunger to learn with strong curiosity.
Pay: $96,000.00-$115,200.00 per year
Benefits:
Company events
Paid time off
Work from home
Education:
Bachelor's Degree (preferred)
Experience:
data engineer: 5 years (preferred)
Work Location: In person
Return
As a Data Engineer, you own the data layer that everything else depends on. That means building and operating the pipelines that move data out of our operational systems and third-party platforms into Snowflake, modeling and aggregating it there, and pushing the results back out to where the business actually uses them: HubSpot for go-to-market, plus our BI and reporting tools. You're the person who makes a number trustworthy. When a leader asks how a cohort of dealerships is performing, or when the AI team needs clean labeled outcomes to train on, your work is what answers the question. This is a build role, not a maintenance role. The warehouse is early enough that you'll shape the models, the conventions, and the tooling.
WHAT YOU'LL DO
- Build and operate reliable pipelines that land data from our operational databases, product systems, and third-party platforms into Snowflake.
- Model and aggregate data in Snowflake into well-documented, trustworthy tables that analysts, leadership, and engineers can build on.
- Sync aggregated data back into HubSpot so go-to-market teams work from accurate, current information.
- Feed and support our BI and reporting tools, and help define the metrics behind them.
- Own data quality end to end: validation, freshness and volume monitoring, alerting, and backfills when something goes wrong.
- Manage schema evolution and pipeline changes without breaking downstream consumers.
- Partner with engineering to make sure v2.0 emits the events and data the warehouse needs, rather than reverse-engineering it after the fact.
- Support the AI side of the business by turning raw conversation and outcome data into clean, labeled datasets.
WHAT WE'RE LOOKING FOR
- Strong SQL. You can write, read, and debug complex analytical SQL, and you care about how it performs.
- Hands-on experience with Snowflake, or a comparable cloud warehouse and the ability to ramp fast.
- Experience building production data pipelines, including orchestration, incremental loads, and idempotent reprocessing.
- Strong Python for data work.
- Experience with dimensional or analytics data modeling, and with a transformation framework such as dbt.
- Experience integrating with SaaS platforms and their APIs. HubSpot experience is a plus, as is CRM or marketing data experience generally.
- Experience with BI tooling and building datasets other people report from.
- Hands-on experience with AWS.
- Excellent debugging skills. You enjoy chasing a problem to its actual root cause, including "why does this number look wrong."
- An AI-first development approach. You are comfortable and effective using Claude as a daily part of how you build, review, and debug, not an occasional novelty.
- Excellent communication skills. You can explain a metric definition to a non-technical stakeholder and get agreement on it.
- Excellent communication skills, including writing clearly about technical decisions.
- A hunger to learn with strong curiosity.
Pay: $96,000.00-$115,200.00 per year
Benefits:
Company events
Paid time off
Work from home
Education:
Bachelor's Degree (preferred)
Experience:
data engineer: 5 years (preferred)
Work Location: In person
Return
