Data Engineer

Job Descripiton - Data Engineer

About the role

We are hiring a Data Engineer to work as part of the PeakTrend team on long-running client engagements. In many of these we act as the client's outsourced data team: they send us a steady flow of requests, and we handle them, from a new report or a changed metric to a broken refresh or a new data feed. You will be one of the people who picks that work up and gets it done.

Each engagement starts with understanding how the client's data is structured, where it comes from, what the business needs from it, and why the current reporting does not deliver. From there you will recommend a way forward and build much of it yourself, from SQL models and data pipelines through to finished dashboards. Once the foundations are sound, the work becomes ongoing: you keep the data healthy, answer new questions as they arise, and build what the client needs next.

A typical engagement might involve a client running Amazon QuickSight over a relational database and a CRM, with calculated fields nobody fully understands, slow or failing dataset refreshes, and several versions of the same metric. You would be the person who works out what is going on, fixes it, and leaves the client with something they can rely on.

This role suits someone who is happy moving between data engineering, analytics and dashboard design in the same week, and who enjoys talking to the people who use the data as much as working with the data itself.

What you will do

Understand the data and the business

• Map a client's source systems, data models and existing reports, and document how they fit together.
• Speak to commercial, operational and leadership stakeholders to establish which questions the data needs to answer and which metrics drive their decisions.
• Find data quality problems, conflicting definitions and unreliable logic, and explain their commercial impact in plain language.
• Write clear recommendations that rank the fixes by value and effort.

Build and maintain data pipelines

• Design and build ETL and ELT processes that extract data from databases, SaaS platforms (Salesforce in particular) and APIs, and load it into a reporting-ready structure.
• Write and tune SQL, including multi-step queries with CTEs and window functions, against production databases such as MariaDB, MySQL and PostgreSQL.
• Add monitoring, testing and alerting so that failed loads and bad data are caught before the client sees them.
• Diagnose refresh and performance problems, such as ingestion timeouts and slow queries, and fix them at the cause.

Deliver dashboards and analysis

• Build and improve dashboards, mainly in Amazon QuickSight but across any client supported tools,, including calculated fields, parameters, cascading filters, conditional formatting and custom visuals.
• Produce analysis on topics such as revenue and ARR, customer growth and churn, product usage and adoption, and sales pipeline performance.
• Present findings to clients and help their teams use the dashboards confidently.

Work AI-first

• Use AI tools as a routine part of the job: drafting and reviewing SQL and Python, debugging, documenting, exploring unfamiliar datasets and preparing client material.
• Check AI output properly before it reaches a client, and know where it tends to go wrong with data work.
• Help us improve our own prompts, skills and templates as you find methods that work.

What we are looking for

Essential

• Strong SQL. You can read an unfamiliar schema, write a correct multi-join query and tell when a result looks wrong.
• Hands-on experience building ETL or ELT pipelines, using Python or a comparable approach.
• Production experience with at least one BI tool. QuickSight is ideal. Power BI, Tableau or Looker experience is welcome if you can pick up QuickSight quickly.
• Working knowledge of AWS data services, such as S3, RDS, Athena or Glue.
• Daily use of AI tools such as Claude, ChatGPT or Copilot in your analysis and engineering work, with examples you can describe in detail.
• Commercial awareness. You ask what a number is for before you build it, and you can explain a technical problem to a non-technical stakeholder.
• Experience working remotely and independently, with clear written communication.

Useful, but not required

• Experience with Salesforce data and its API, including extracting objects such as accounts, opportunities and subscriptions.
• Experience with dbt or a similar transformation framework, or a modern warehouse such as Snowflake, BigQuery or Redshift.
• Background in SaaS metrics, such as ARR, retention and churn.
• Previous consultancy or client-facing delivery experience.
• Experience building with LLM APIs or automation tools.

Job Type: Part-time/Fulltime

Benefits:

• Company events
• Pay raise
• Work from home

Application Question(s): Please answer these questions to qualify.

• What is your salary expectation? And if your expected pay is higher than what we’re offering, would you still be open to considering this role?"
• The role requires strong communication with clients, as well as working during UK hours. Are you comfortable with that?
• Do you have your own working laptop and a reliable internet connection of atleast 20mbps?

Work Location: Remote.

If you have a passion for sales and want a role where your income reflects your performance, we'd love to hear from you.

Pay: Php80,000.00 per month

Benefits:

• Company events
• Pay raise
• Work from home

Application Question(s):

• 1. Are you currently residing in Metro Manila?
• Do you own a working laptop and a reliable internet connection of atleast 20mbps?

Work Location: Remote