高级数据工程师

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 (English, written and spoken).

Bonus points

• Domain experience in payments, FinTech, or financial-services data — familiarity with concepts such as interchange, scheme/network fees, take rate, chargebacks, authorization rates, or surcharging.

• Experience integrating payment-processor data (e.g. Worldpay, Adyen, Stripe) and normalizing heterogeneous processor data into a single model.

• Experience supporting BI/analytics teams and self-service reporting tools (e.g. Power BI, Tableau, Looker, Sigma).

• Exposure to analytics engineering or hands-on work with forecasting / cohort-based analytical models.

• Data contracts and governance practices (dbt exposures, contracts/tests, semantic layers).

What’s in it for You
Reveal great tech solutions
Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.
Experience an agile and flexible working environment
Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.
Embrace the opportunity for personal and professional growth
Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more.
Be among like-minded people
Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.
Interview steps

• Pre-Screening with the recruiter (up to 30 min)

• Technical Interview (up to 90 min)

• Interview with Manager (45 min)

Originally posted on Himalayas