How would you handle a conflict with a teammate during a high-stakes project?

I would handle a conflict with a teammate by addressing it directly and privately, focusing on understanding the root cause and collaboratively finding a solution that prioritizes project success and maintains team cohesion.

Approach to Conflict Resolution

My first step is to initiate a private 1:1 conversation, ensuring a safe space for open dialogue. I actively listen to understand my teammate's perspective, rationale, and concerns, rather than immediately defending my own. Often, conflicts stem from differing interpretations of requirements, technical trade-offs, or even personal communication styles. By focusing on the underlying data, technical constraints (e.g., Spark shuffle performance, Snowflake micro-partitioning implications), or business goals, we can move towards an objective discussion. If a consensus isn't quickly reached, I'd propose exploring alternative solutions, perhaps a hybrid approach, or suggest involving a neutral third party like a tech lead or manager to mediate and provide an objective viewpoint. Once a decision is made, it's crucial to document it and present a united front to the wider team.

Concrete Example

During a high-stakes project with a two-week go-live, my teammate and I disagreed on the optimal deduplication strategy for a critical data pipeline. My teammate advocated for a simple DISTINCT operation for perceived speed, while I argued for a ROW_NUMBER()-based approach to ensure the latest record was always selected, crucial for data integrity.

The conflict centered on performance versus data accuracy. During our 1:1, I listened to their concerns about potential Spark shuffle costs with ROW_NUMBER() on large datasets. I then explained the business impact of stale data and demonstrated how a QUALIFY clause with ROW_NUMBER() could be optimized, potentially leveraging existing table clustering keys in systems like Snowflake or Delta Lake to minimize data movement.

-- Hybrid deduplication strategy for latest record
WITH source_data AS (
  SELECT
    id,
    value,
    updated_at,
    ROW_NUMBER() OVER (PARTITION BY id ORDER BY updated_at DESC) as rn
  FROM raw_events
)
SELECT id, value, updated_at
FROM source_data
WHERE rn = 1;

We agreed on a hybrid ROW_NUMBER() approach, carefully partitioning by the natural key and ordering by the timestamp, which satisfied both performance and accuracy requirements. We documented the decision, including the trade-offs and rationale, and presented it as a unified team. The pipeline shipped on time, and our working relationship was strengthened through the collaborative resolution.

In the interview, also mention proactive steps you take to prevent conflicts, such as clear communication, early alignment on technical designs, and regular feedback.