Senior Data Engineer, Ads Data (AI Native)

This

position

is

listed

on

behalf

of

a

partner

company,

who

manages

all

applications

and

next

steps.

Our

partner

is

looking

for

a

Senior

Data

Engineer,

Ads

Data

(AI

Native)

based

in

the

United

States

.

Join

a

fast-growing,

remote-first

technology

organization

dedicated

to

helping

families

stay

connected

and

protected

through

innovative

digital

products

and

services.

As

a

Senior

Data

Engineer,

you

will

take

ownership

of

critical

data

infrastructure

supporting

advertising

analytics,

campaign

performance,

and

business

intelligence.

You

will

design,

optimize,

and

scale

data

pipelines

that

transform

billions

of

data

points

into

reliable,

actionable

insights.

Working

closely

with

analysts,

advertising

strategists,

and

sales

teams,

you

will

help

create

trusted

datasets

and

standardized

metrics

that

drive

smarter

business

decisions.

You

will

leverage

modern

cloud

technologies

and

AI-powered

development

tools

to

improve

engineering

efficiency,

platform

reliability,

and

scalability.

This

is

an

opportunity

to

combine

deep

technical

expertise,

cross-functional

collaboration,

and

AI-native

innovation

while

making

a

meaningful

impact

within

a

globally

Accountabilities

Build

and

maintain

scalable

data

infrastructure

Enhance,

extend,

and

operate

batch

and

streaming

pipelines,

Delta

Lake

tables,

and

data

workflows

on

Databricks

to

support

growing

data

volumes

and

evolving

business

requirements.

Develop

business-focused

data

products:

Collaborate

with

business

analysts,

advertising

strategists,

and

sales

teams

to

translate

their

needs

into

reliable

datasets,

campaign

performance

reports,

audience

insights,

and

revenue

analytics.

Own

data

modeling

and

metrics:

Build

and

maintain

dbt

models,

automated

tests,

curated

Silver

and

Gold

datasets,

and

semantic

layers

to

ensure

consistent

and

trusted

business

metrics

across

the

organization.

Optimize

performance

and

infrastructure

costs:

Improve

Spark

and

Databricks

workloads

through

query

optimization,

partitioning,

cluster

sizing,

shuffle

management,

and

efficient

resource

allocation.

Manage

cloud

infrastructure:

Maintain

and

automate

Databricks

and

AWS

infrastructure

using

Terraform,

ensuring

secure,

scalable,

and

reliable

data

platform

operations.

Integrate

multiple

data

sources

Connect,

consolidate,

and

reconcile

data

from

advertising

platforms,

CRM

systems,

external

partners,

and

internal

applications

while

supporting

migrations

from

legacy

reporting

solutions.

Strengthen

data

quality

and

reliability:

Implement

monitoring,

data

lineage,

SLAs,

alerting,

automated

testing,

and

data

contracts.

Lead

root-cause

analysis

and

resolve

issues

affecting

data

availability

and

accuracy.

Establish

engineering

best

practices:

Promote

effective

version

control,

CI/CD,

code

reviews,

testing,

and

documentation

while

mentoring

engineers

and

contributing

to

the

team's

technical

roadmap.

Ensure

data

governance

and

compliance:

Apply

appropriate

privacy

controls,

security

standards,

and

access

management

practices

to

protect

sensitive

information

and

meet

GDPR,

CCPA,

and

SOX

requirements.

Advance

AI-native

engineering

capabilities:

Build

tools,

workflows,

and

AI

agents

that

provide

LLMs

with

additional

context,

helping

accelerate

development,

debugging,

code

generation,

and

system

maintenance.

Drive

continuous

improvement:

Take

ownership

of

foundational

pipelines

and

data

models,

reduce

processing

times

and

infrastructure

costs,

and

enable

stakeholders

to

access

trusted

information

independently.

Requirements

At

least

5

years

of

professional

data

engineering

experience

,

with

a

proven

track

record

of

building

and

operating

production-grade

data

platforms

at

enterprise

scale.

Advanced

hands-on

expertise

in

Apache

Spark

,

including

PySpark

and/or

Scala,

with

strong

knowledge

of

partitioning,

How Jobgether works

• We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
• We appreciate your interest and wish you the best!
• Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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