Principal Data Engineer

We are seeking a Principal Data Engineer excited about delivering data solutions that drive business outcomes. Through proprietary software and AI, Sleek automates back-office processes to empower micro SMEs. We aim to give Entrepreneurs time back to focus on growth and customer relationships. Sleek operates across Corporate Secretary, Accounting & Bookkeeping, and FinTech payments, with offices in Singapore, Hong Kong, Australia and the UK, a team of around 500 staff, and ~15,000 customers. We are backed by world-class investors and have recently raised Series B financing. Sleek is a proudly certified B Corp with a commitment to sustainability and responsible growth.

Work closely with cross-functional teams to translate our business vision into impactful data solutions. Align data architecture with strategic goals, bridging business insights and technical execution by tackling complex data integration, modeling, and security challenges. Shape the data roadmap and empower the team to deliver scalable, high-quality data products every day.

• Architecture & Design: Define the overall greenfield data architecture (batch + streaming) using GCP BigQuery; establish best practices for ingestion, transformation, data quality, and governance.
• Data Ingestion & Processing: Lead ETL/ELT pipeline design and implementation; ingestion via Datastream, Pub/Sub, Dataflow, Airbyte, Fivetran, Rivery; storage & compute in BigQuery, GCS; transformations with dbt, Cloud Composer (Airflow), Dagster; ensure data quality with dbt tests, Great Expectations/Soda, and monitoring.
• Governance & Security: Implement Dataplex & Data Catalog for metadata, lineage, and discoverability; define IAM policies, row/column-level security, DLP strategies, and compliance controls.
• Monitoring, Observability & Reliability: Define and enforce SLAs, SLOs, and SLIs for pipelines and data products; implement cloud-based observability tooling; ensure pipeline resilience (idempotency, retries, backfills, incremental loads); establish disaster recovery and high availability (multi-region storage, backup/restore).
• Analytics Enablement: Partner with BI/analytics teams to deliver governed self-service through Looker and Looker Studio; support squad-level data product ownership with clear contracts and SLAs.
• Team Leadership: Mentor a small data engineering team; set coding standards, CI/CD, and operational practices.
• Cross-functional Collaboration: Collaborate with squads, product managers, and leadership to deliver trusted data assets.

• 10+ years of experience in data engineering, architecture, or platform roles.
• Strong expertise in the GCP data stack: BigQuery, GCS, Dataplex, Data Catalog, Pub/Sub, Dataflow.
• Hands-on experience building ETL/ELT pipelines with dbt and orchestration (Composer/Airflow/Dagster).
• Deep knowledge of data modeling, warehousing, and partitioning/clustering strategies.
• Experience with monitoring, reliability engineering, and observability for data systems.
• Familiarity with data governance, lineage, and security policies (IAM, DLP, encryption).
• Strong SQL skills and Python proficiency for data engineering.

• Experience with Snowflake, Databricks, AWS (Redshift, Glue, Athena), or Azure Synapse.
• Knowledge of open-source catalogs (DataHub, Amundsen, OpenMetadata).
• Background in streaming systems (Kafka, Kinesis, Flink, Beam).
• Exposure to data observability tools (Monte Carlo, Bigeye, Datafold, Databand).
• Prior work with Looker, Hex, or other BI/analytics tools.
• Startup or scale-up experience in fast-moving, resource-constrained environments.

We value Ownership, Humility, Structured Thinking, Attention to detail, and Excellent listening & clear communication. These attributes help teams collaborate effectively in a diverse, global environment.

The successful candidate will participate in multiple interview stages (order may vary). The process is expected to last no more than 3 weeks from start to finish. Interviews may be conducted via video or in person depending on location and role.

• Screening call: 30-minute chat with Talent Acquisition.
• Technical screening: 30-minute call with a Senior Data Engineer.
• Technical competency panel: 60-minute interview with two Senior Engineers focusing on Python and SQL.
• Behavioural panel interview: 60-minute conversation with business leaders.
• Final interview: 60-minute discussion with our CTO.
• Offer + references: Non-binding verbal or email offer followed by reference checks.
• Background checks: Sleek may perform background checks (education, criminal history, political exposure, bankruptcy/adverse credit) as required by role; consent obtained. Adverse results may affect probation.

By submitting an application, you confirm you have read and agree to our Data Privacy Statement for Candidates found at sleek.com.

We offer a range of benefits, including:

• Humility and kindness: A culture of inclusivity and respect.
• Flexibility: Remote work options; up to one month per year remote from anywhere in the world.
• Financial benefits: Competitive salaries, generous PTO, and employee share ownership where applicable.
• Personal growth: Responsibility, autonomy, and ongoing training; involvement in AI initiatives and a regional AI excellence hub.

Sleek is a certified B Corp with a mission toward sustainable, inclusive growth and environmental stewardship. We have planted trees, reduced paper usage, and aim for carbon neutrality by 2030.

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Other

Industries: IT Services and IT Consulting