Staff/Senior Data Engineer

This

position

is

listed

on

behalf

of

a

partner

company,

who

manages

all

applications

and

next

steps.

Our

partner

is

looking

for

a

Staff/Senior

Data

Engineer

based

in

the

United

States

.

In

this

role,

you

will

take

ownership

of

the

design,

development,

and

scaling

of

a

modern

data

and

analytics

infrastructure

within

an

innovative

robotics

and

AI

environment.

You

will

build

and

optimize

cloud-based

data

pipelines

and

warehouse

solutions

that

transform

complex

data

into

reliable,

actionable

insights.

Working

closely

with

data

scientists,

analytics

engineers,

and

application

database

teams,

you

will

establish

best

practices

that

support

scalable

data

operations.

You

will

play

a

key

role

in

enabling

efficient

data

exchange

with

external

clients

while

ensuring

data

quality,

security,

and

regulatory

compliance.

The

position

offers

the

opportunity

to

influence

technical

architecture,

improve

cloud

efficiency,

and

strengthen

the

organization's

data

capabilities.

Depending

on

your

experience

and

technical

expertise,

the

role

may

be

leveled

at

Senior

or

Staff

level.

Accountabilities

Design,

implement,

and

scale

the

organization's

data

warehouse

and

analytics

infrastructure,

creating

a

reliable

foundation

for

enterprise-wide

data

consumption.

Build

and

maintain

data

ingestion

pipelines

that

integrate

information

from

PostgreSQL,

Google

Cloud

Storage,

Jira,

web

analytics

platforms,

and

other

sources

into

BigQuery.

Develop

and

manage

data

transformation

workflows

using

dbt,

converting

raw

datasets

into

structured,

user-friendly

data

marts

that

support

AI,

business

intelligence,

and

analytics

applications.

Define

and

implement

scalable

data

exchange

strategies,

enabling

reliable

inbound

data

feeds,

including

product

catalogs

and

planograms,

as

well

as

large-scale

outbound

data

deliveries

and

cloud-native

data

sharing

with

clients.

Establish

infrastructure

and

processes

that

ensure

external

data

transfers

are

scalable,

secure,

traceable,

and

efficient.

Monitor

cloud

infrastructure

and

data

warehouse

spending,

implementing

cost

controls

and

optimization

strategies

to

maintain

predictable

operating

expenses.

Collaborate

with

application

database

teams

to

improve

cloud

architecture,

leverage

infrastructure

synergies,

accelerate

access

to

insights,

and

reduce

overall

cloud

costs.

Establish

comprehensive

data

quality

frameworks

using

dbt

testing

capabilities,

ensuring

the

accuracy,

consistency,

and

reliability

of

analytical

datasets.

Develop

and

maintain

standardized

metric

definitions,

data

documentation,

and

governance

practices

that

make

trusted

data

accessible

across

the

organization.

Champion

DataOps

principles

and

empower

analytics

engineers

and

data

scientists

to

independently

develop

and

manage

reliable

metrics

and

analytical

workflows.

Implement

and

maintain

appropriate

access

controls

and

permissions

across

data

consumption

environments.

Ensure

data

infrastructure

complies

with

GDPR,

personally

identifiable

information

(PII)

requirements,

SOC

2,

and

other

relevant

security

and

regulatory

standards.

Requirements:

At

least

5

years

of

hands-on

experience

working

with

SQL,

BigQuery,

Terraform,

Apache

Beam,

Airflow,

and

Google

Cloud

Platform

(GCP).

Demonstrated

experience

designing,

implementing,

and

managing

end-to-end

data

warehouse

solutions.

Strong

expertise

in

data

modeling

and

developing

analytical

data

architectures

that

support

business

intelligence

and

advanced

analytics

use

cases.

Practical

experience

with

dbt

and

event-driven

analytics

is

highly

desirable.

Strong

proficiency

in

SQL

and

Python,

with

the

ability

to

develop

and

maintain

scalable

data

pipelines

and

transformation

processes.

Solid

understanding

of

cloud

infrastructure

architecture,

including

the

strengths,

limitations,

and

use

cases

of

transactional

versus

analytical

da

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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