Senior Data Engineer

At SPD Technology , we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

And now we are looking for a Senior Data Engineer to join us as part of our team.
About the role

We are looking for a Senior Data Engineer to lead the build of an automated payments reporting and analytics platform for a client in the payments space. Today, revenue reporting for this business depends on manual journal entries and manual assembly of results — the general ledger and BI reporting do not reconcile without human intervention, and reporting is too aggregated to explain performance.

Your mission is to replace that with a consistent, automated data flow: daily pipelines that land processor, CRM, and ERP data into a cloud data warehouse, post automatically to the general ledger, and feed a reporting layer granular enough to decompose any variance to budget down to its root cause. This is a high-ownership role with direct visibility to finance and business stakeholders, where the quality of your data models directly determines whether the business can trust its numbers.
Technical Stack

Core: Snowflake, dbt, SQL, Python, a modern orchestrator (Airflow / Dagster / Prefect), Git + CI/CD.

Source systems in scope: multiple payment processors and a core payments API, a CRM (customer & pricing attributes), and an ERP/general ledger. A BI tool renders the end-user dashboards on top of the modeled data.
As a qualified expert You will

- Design and build automated, reliable ELT pipelines that integrate data from multiple source systems (payment processors, CRM, and ERP) into a cloud data warehouse on a daily cadence.

- Automate financial reporting to the general ledger that reconciles with the reporting layer by design, replacing manual, error-prone processes.

- Build and maintain a data-mapping layer that resolves customer identity across systems and rolls transactions up to a single customer key.

- Model clean, well-documented data marts that make business performance explainable and support drill-down and variance analysis.

- Deliver the data models that power a KPI and forecasting dashboard for finance and business stakeholders.

- Ensure pipelines are robust and auditable with monitoring, data-quality checks, and alerting so issues are caught before reporting is consumed.

- Collaborate with BI, finance, and integration partners to turn business requirements into reliable data products and define phased delivery.

We’re looking for you if you have

- 5+ years of professional experience in data engineering, with a track record of owning production data pipelines end to end.

- Expert-level SQL — complex analytical queries, window functions, query optimization, and dimensional / star-schema data modeling.

- Hands-on experience on a modern cloud data warehouse, ideally Snowflake (or comparable: BigQuery, Redshift, Databricks).

- Strong experience with dbt (or an equivalent ELT transformation framework) for transformation and building tested, documented, version-controlled data models.

- Proven experience building and scheduling ELT/ETL pipelines using a workflow orchestrator (e.g. Airflow, Dagster, Prefect) and designing idempotent, re-runnable, incremental loads.

- Experience implementing data-quality testing, monitoring, and alerting as first-class parts of a pipeline.

- Strong communication skills with the ability to work directly with finance/business stakeholders, clarify requirements, and explain data-model decisions clearly (Englis