Data Engineer Client Data Operations

This

position

is

listed

on

behalf

of

a

partner

company,

who

manages

all

applications

and

next

steps.

Our

partner

is

looking

for

a

Data

Engineer

Client

Data

Operations

based

in

the

United

States

.

The

Data

Engineer

will

play

a

key

role

in

building,

maintaining,

and

optimizing

the

data

infrastructure

that

supports

client

marketing

campaigns,

audience

management,

and

business

reporting.

This

hands-on

position

focuses

on

onboarding

new

client

data,

transforming

complex

and

inconsistent

source

files

into

reliable

production-ready

datasets,

and

ensuring

data

pipelines

operate

efficiently.

You

will

take

ownership

of

production

workflows,

troubleshoot

technical

issues,

and

develop

scalable

ingestion

processes

using

modern

cloud

technologies.

Working

closely

with

analytics,

campaign,

account,

and

technical

teams,

you

will

help

ensure

data

accuracy,

security,

and

seamless

campaign

delivery.

This

is

an

individual

contributor

role

offering

significant

autonomy

and

the

opportunity

to

improve

operational

processes

within

a

growing,

data-driven

environment.

The

position

is

fully

remote

across

the

United

States,

with

a

preference

for

candidates

located

in

the

Dallas,

Texas

area.

Accountabilities:

Client

Data

Onboarding:

Set

up

and

manage

incoming

data

feeds

from

client

and

vendor

systems,

including

SFTP

connections

and

scheduled

file

deliveries.

Analyze

source

files,

identify

missing

fields,

inconsistent

formats,

and

schema

changes,

and

map

incoming

information

into

established

database

structures.

Data

Validation

and

Processing:

Develop

validation,

identity

matching,

and

data

preparation

processes,

including

record-count

reconciliation,

LTID

assignment,

and

CASS/NCOA

processing

when

applicable.

Ensure

data

quality

before

it

enters

production

workflows.

Pipeline

Development

Build,

maintain,

and

optimize

scalable

data

pipelines

using

SQL,

Python,

and

Spark

to

support

new

direct

mail

and

digital

marketing

clients.

Establish

reusable

data

structures

and

avoid

unnecessary

one-off

solutions.

Workflow

Automation:

Configure

scheduled

jobs,

file

monitoring,

transformations,

testing,

and

automated

alerts

to

minimize

manual

intervention

and

improve

pipeline

reliability.

Production

Monitoring

and

Troubleshooting:

Own

daily

monitoring

and

maintenance

of

Databricks

workflows,

AWS

jobs,

and

related

data

tools.

Investigate

and

resolve

pipeline

failures,

schema

changes,

expired

credentials,

broken

dependencies,

stale

data,

and

vendor-related

issues.

Campaign

and

Mail

Production:

Manage

routine

audience

and

direct

mail

production

activities,

including

data

suppression,

address

hygiene,

record

reconciliation,

quality

control,

and

preparation

of

files

for

external

vendors,

following

established

approval

procedures.

Operational

Documentation:

Create

and

maintain

clear

documentation

covering

data

sources,

transformations,

validation

processes,

outputs,

troubleshooting

procedures,

and

recovery

workflows.

Data

Security

and

Compliance:

Identify

sensitive

information

and

apply

approved

privacy,

access,

and

data-handling

policies.

Escalate

ambiguous

data

governance

or

privacy

questions

to

the

appropriate

stakeholders.

Cross-Functional

Collaboration:

Work

closely

with

the

Senior

Analytics

Engineer

to

provide

clean,

consistent,

well-documented

datasets

for

downstream

modeling,

analysis,

and

reporting.

Stakeholder

Communication:

Collaborate

with

campaign,

account

management,

and

technical

teams

to

clarify

requirements,

resolve

data

issues,

communicate

delivery

risks,

and

recommend

appropriate

solutions.

Continuous

Improvement:

Identify

opportunities

to

strengthen

pipeline

monitoring,

automate

recurring

tasks,

improve

operational

efficiency,

and

reduce

dependency

on

manual

troubleshooting.

Requirements:

Several

years

of

hands-on

data

engineering

experience,

ideally

4+

years

,

including

building,

maintaining,

and

operating

production

data

pipelines.

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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